diff --git a/en/go/resources/fine_tuning/index.md b/en/go/resources/fine_tuning/index.md new file mode 100644 index 0000000..307a64e --- /dev/null +++ b/en/go/resources/fine_tuning/index.md @@ -0,0 +1,10543 @@ +# Fine Tuning + +# Methods + +## Domain Types + +### Dpo Hyperparameters + +- `type DpoHyperparametersResp struct{…}` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Dpo Method + +- `type DpoMethod struct{…}` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Reinforcement Hyperparameters + +- `type ReinforcementHyperparametersResp struct{…}` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + +### Reinforcement Method + +- `type ReinforcementMethod struct{…}` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + +### Supervised Hyperparameters + +- `type SupervisedHyperparametersResp struct{…}` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Supervised Method + +- `type SupervisedMethod struct{…}` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +# Jobs + +## Create fine-tuning job + +`client.FineTuning.Jobs.New(ctx, body) (*FineTuningJob, error)` + +**post** `/fine_tuning/jobs` + +Create fine-tuning job + +### Parameters + +- `body FineTuningJobNewParams` + + - `Model param.Field[FineTuningJobNewParamsModel]` + + The name of the model to fine-tune. You can select one of the + [supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned). + + - `string` + + - `type FineTuningJobNewParamsModel string` + + The name of the model to fine-tune. You can select one of the + [supported models](https://platform.openai.com/docs/guides/fine-tuning#which-models-can-be-fine-tuned). + + - `const FineTuningJobNewParamsModelBabbage002 FineTuningJobNewParamsModel = "babbage-002"` + + - `const FineTuningJobNewParamsModelDavinci002 FineTuningJobNewParamsModel = "davinci-002"` + + - `const FineTuningJobNewParamsModelGPT3_5Turbo FineTuningJobNewParamsModel = "gpt-3.5-turbo"` + + - `const FineTuningJobNewParamsModelGPT4oMini FineTuningJobNewParamsModel = "gpt-4o-mini"` + + - `TrainingFile param.Field[string]` + + The ID of an uploaded file that contains training data. + + See [upload file](https://platform.openai.com/docs/api-reference/files/create) for how to upload a file. + + Your dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose `fine-tune`. + + The contents of the file should differ depending on if the model uses the [chat](https://platform.openai.com/docs/api-reference/fine-tuning/chat-input), [completions](https://platform.openai.com/docs/api-reference/fine-tuning/completions-input) format, or if the fine-tuning method uses the [preference](https://platform.openai.com/docs/api-reference/fine-tuning/preference-input) format. + + See the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details. + + - `Hyperparameters param.Field[FineTuningJobNewParamsHyperparameters]` + + The hyperparameters used for the fine-tuning job. + This value is now deprecated in favor of `method`, and should be passed in under the `method` parameter. + + - `BatchSize FineTuningJobNewParamsHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobNewParamsHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobNewParamsHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Integrations param.Field[[]FineTuningJobNewParamsIntegration]` + + A list of integrations to enable for your fine-tuning job. + + - `Type Wandb` + + The type of integration to enable. Currently, only "wandb" (Weights and Biases) is supported. + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobNewParamsIntegrationWandb` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata param.Field[Metadata]` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method param.Field[FineTuningJobNewParamsMethod]` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobNewParamsMethodTypeSupervised FineTuningJobNewParamsMethodType = "supervised"` + + - `const FineTuningJobNewParamsMethodTypeDpo FineTuningJobNewParamsMethodType = "dpo"` + + - `const FineTuningJobNewParamsMethodTypeReinforcement FineTuningJobNewParamsMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Seed param.Field[int64]` + + The seed controls the reproducibility of the job. Passing in the same seed and job parameters should produce the same results, but may differ in rare cases. + If a seed is not specified, one will be generated for you. + + - `Suffix param.Field[string]` + + A string of up to 64 characters that will be added to your fine-tuned model name. + + For example, a `suffix` of "custom-model-name" would produce a model name like `ft:gpt-4o-mini:openai:custom-model-name:7p4lURel`. + + - `ValidationFile param.Field[string]` + + The ID of an uploaded file that contains validation data. + + If you provide this file, the data is used to generate validation + metrics periodically during fine-tuning. These metrics can be viewed in + the fine-tuning results file. + The same data should not be present in both train and validation files. + + Your dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`. + + See the [fine-tuning guide](https://platform.openai.com/docs/guides/model-optimization) for more details. + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + fineTuningJob, err := client.FineTuning.Jobs.New(context.TODO(), openai.FineTuningJobNewParams{ + Model: openai.FineTuningJobNewParamsModelGPT4oMini, + TrainingFile: "file-abc123", + }) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", fineTuningJob.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## List fine-tuning jobs + +`client.FineTuning.Jobs.List(ctx, query) (*CursorPage[FineTuningJob], error)` + +**get** `/fine_tuning/jobs` + +List fine-tuning jobs + +### Parameters + +- `query FineTuningJobListParams` + + - `After param.Field[string]` + + Identifier for the last job from the previous pagination request. + + - `Limit param.Field[int64]` + + Number of fine-tuning jobs to retrieve. + + - `Metadata param.Field[map[string, string]]` + + Optional metadata filter. To filter, use the syntax `metadata[k]=v`. Alternatively, set `metadata=null` to indicate no metadata. + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + page, err := client.FineTuning.Jobs.List(context.TODO(), openai.FineTuningJobListParams{ + + }) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", page) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } + } + ], + "has_more": true, + "object": "list" +} +``` + +## Retrieve fine-tuning job + +`client.FineTuning.Jobs.Get(ctx, fineTuningJobID) (*FineTuningJob, error)` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}` + +Retrieve fine-tuning job + +### Parameters + +- `fineTuningJobID string` + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + fineTuningJob, err := client.FineTuning.Jobs.Get(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F") + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", fineTuningJob.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## List fine-tuning events + +`client.FineTuning.Jobs.ListEvents(ctx, fineTuningJobID, query) (*CursorPage[FineTuningJobEvent], error)` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}/events` + +List fine-tuning events + +### Parameters + +- `fineTuningJobID string` + +- `query FineTuningJobListEventsParams` + + - `After param.Field[string]` + + Identifier for the last event from the previous pagination request. + + - `Limit param.Field[int64]` + + Number of events to retrieve. + +### Returns + +- `type FineTuningJobEvent struct{…}` + + Fine-tuning job event object + + - `ID string` + + The object identifier. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Level FineTuningJobEventLevel` + + The log level of the event. + + - `const FineTuningJobEventLevelInfo FineTuningJobEventLevel = "info"` + + - `const FineTuningJobEventLevelWarn FineTuningJobEventLevel = "warn"` + + - `const FineTuningJobEventLevelError FineTuningJobEventLevel = "error"` + + - `Message string` + + The message of the event. + + - `Object FineTuningJobEvent` + + The object type, which is always "fine_tuning.job.event". + + - `const FineTuningJobEventFineTuningJobEvent FineTuningJobEvent = "fine_tuning.job.event"` + + - `Data any` + + The data associated with the event. + + - `Type FineTuningJobEventType` + + The type of event. + + - `const FineTuningJobEventTypeMessage FineTuningJobEventType = "message"` + + - `const FineTuningJobEventTypeMetrics FineTuningJobEventType = "metrics"` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + page, err := client.FineTuning.Jobs.ListEvents( + context.TODO(), + "ft-AF1WoRqd3aJAHsqc9NY7iL8F", + openai.FineTuningJobListEventsParams{ + + }, + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", page) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "level": "info", + "message": "message", + "object": "fine_tuning.job.event", + "data": {}, + "type": "message" + } + ], + "has_more": true, + "object": "list" +} +``` + +## Cancel fine-tuning + +`client.FineTuning.Jobs.Cancel(ctx, fineTuningJobID) (*FineTuningJob, error)` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/cancel` + +Cancel fine-tuning + +### Parameters + +- `fineTuningJobID string` + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + fineTuningJob, err := client.FineTuning.Jobs.Cancel(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F") + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", fineTuningJob.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Pause fine-tuning + +`client.FineTuning.Jobs.Pause(ctx, fineTuningJobID) (*FineTuningJob, error)` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/pause` + +Pause fine-tuning + +### Parameters + +- `fineTuningJobID string` + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + fineTuningJob, err := client.FineTuning.Jobs.Pause(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F") + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", fineTuningJob.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Resume fine-tuning + +`client.FineTuning.Jobs.Resume(ctx, fineTuningJobID) (*FineTuningJob, error)` + +**post** `/fine_tuning/jobs/{fine_tuning_job_id}/resume` + +Resume fine-tuning + +### Parameters + +- `fineTuningJobID string` + +### Returns + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + fineTuningJob, err := client.FineTuning.Jobs.Resume(context.TODO(), "ft-AF1WoRqd3aJAHsqc9NY7iL8F") + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", fineTuningJob.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "created_at": 0, + "error": { + "code": "code", + "message": "message", + "param": "param" + }, + "fine_tuned_model": "fine_tuned_model", + "finished_at": 0, + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + }, + "model": "model", + "object": "fine_tuning.job", + "organization_id": "organization_id", + "result_files": [ + "file-abc123" + ], + "seed": 0, + "status": "validating_files", + "trained_tokens": 0, + "training_file": "training_file", + "validation_file": "validation_file", + "estimated_finish": 0, + "integrations": [ + { + "type": "wandb", + "wandb": { + "project": "my-wandb-project", + "entity": "entity", + "name": "name", + "tags": [ + "custom-tag" + ] + } + } + ], + "metadata": { + "foo": "string" + }, + "method": { + "type": "supervised", + "dpo": { + "hyperparameters": { + "batch_size": "auto", + "beta": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + }, + "reinforcement": { + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + }, + "hyperparameters": { + "batch_size": "auto", + "compute_multiplier": "auto", + "eval_interval": "auto", + "eval_samples": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto", + "reasoning_effort": "default" + } + }, + "supervised": { + "hyperparameters": { + "batch_size": "auto", + "learning_rate_multiplier": "auto", + "n_epochs": "auto" + } + } + } +} +``` + +## Domain Types + +### Fine Tuning Job + +- `type FineTuningJob struct{…}` + + The `fine_tuning.job` object represents a fine-tuning job that has been created through the API. + + - `ID string` + + The object identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Error FineTuningJobError` + + For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure. + + - `Code string` + + A machine-readable error code. + + - `Message string` + + A human-readable error message. + + - `Param string` + + The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific. + + - `FineTunedModel string` + + The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running. + + - `FinishedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running. + + - `Hyperparameters FineTuningJobHyperparameters` + + The hyperparameters used for the fine-tuning job. This value will only be returned when running `supervised` jobs. + + - `BatchSize FineTuningJobHyperparametersBatchSizeUnion` + + Number of examples in each batch. A larger batch size means that model parameters + are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier FineTuningJobHyperparametersLearningRateMultiplierUnion` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid + overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs FineTuningJobHyperparametersNEpochsUnion` + + The number of epochs to train the model for. An epoch refers to one full cycle + through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Model string` + + The base model that is being fine-tuned. + + - `Object FineTuningJob` + + The object type, which is always "fine_tuning.job". + + - `const FineTuningJobFineTuningJob FineTuningJob = "fine_tuning.job"` + + - `OrganizationID string` + + The organization that owns the fine-tuning job. + + - `ResultFiles []string` + + The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `Seed int64` + + The seed used for the fine-tuning job. + + - `Status FineTuningJobStatus` + + The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`. + + - `const FineTuningJobStatusValidatingFiles FineTuningJobStatus = "validating_files"` + + - `const FineTuningJobStatusQueued FineTuningJobStatus = "queued"` + + - `const FineTuningJobStatusRunning FineTuningJobStatus = "running"` + + - `const FineTuningJobStatusSucceeded FineTuningJobStatus = "succeeded"` + + - `const FineTuningJobStatusFailed FineTuningJobStatus = "failed"` + + - `const FineTuningJobStatusCancelled FineTuningJobStatus = "cancelled"` + + - `TrainedTokens int64` + + The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running. + + - `TrainingFile string` + + The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `ValidationFile string` + + The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents). + + - `EstimatedFinish int64` + + The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running. + + - `Integrations []FineTuningJobWandbIntegrationObject` + + A list of integrations to enable for this fine-tuning job. + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + + - `Metadata Metadata` + + Set of 16 key-value pairs that can be attached to an object. This can be + useful for storing additional information about the object in a structured + format, and querying for objects via API or the dashboard. + + Keys are strings with a maximum length of 64 characters. Values are strings + with a maximum length of 512 characters. + + - `Method FineTuningJobMethod` + + The method used for fine-tuning. + + - `Type string` + + The type of method. Is either `supervised`, `dpo`, or `reinforcement`. + + - `const FineTuningJobMethodTypeSupervised FineTuningJobMethodType = "supervised"` + + - `const FineTuningJobMethodTypeDpo FineTuningJobMethodType = "dpo"` + + - `const FineTuningJobMethodTypeReinforcement FineTuningJobMethodType = "reinforcement"` + + - `Dpo DpoMethod` + + Configuration for the DPO fine-tuning method. + + - `Hyperparameters DpoHyperparametersResp` + + The hyperparameters used for the DPO fine-tuning job. + + - `BatchSize DpoHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Beta DpoHyperparametersBetaUnionResp` + + The beta value for the DPO method. A higher beta value will increase the weight of the penalty between the policy and reference model. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `LearningRateMultiplier DpoHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs DpoHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `Reinforcement ReinforcementMethod` + + Configuration for the reinforcement fine-tuning method. + + - `Grader ReinforcementMethodGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `Hyperparameters ReinforcementHyperparametersResp` + + The hyperparameters used for the reinforcement fine-tuning job. + + - `BatchSize ReinforcementHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ComputeMultiplier ReinforcementHyperparametersComputeMultiplierUnionResp` + + Multiplier on amount of compute used for exploring search space during training. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `EvalInterval ReinforcementHyperparametersEvalIntervalUnionResp` + + The number of training steps between evaluation runs. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `EvalSamples ReinforcementHyperparametersEvalSamplesUnionResp` + + Number of evaluation samples to generate per training step. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier ReinforcementHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs ReinforcementHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `ReasoningEffort ReinforcementHyperparametersReasoningEffort` + + Level of reasoning effort. + + - `const ReinforcementHyperparametersReasoningEffortDefault ReinforcementHyperparametersReasoningEffort = "default"` + + - `const ReinforcementHyperparametersReasoningEffortLow ReinforcementHyperparametersReasoningEffort = "low"` + + - `const ReinforcementHyperparametersReasoningEffortMedium ReinforcementHyperparametersReasoningEffort = "medium"` + + - `const ReinforcementHyperparametersReasoningEffortHigh ReinforcementHyperparametersReasoningEffort = "high"` + + - `Supervised SupervisedMethod` + + Configuration for the supervised fine-tuning method. + + - `Hyperparameters SupervisedHyperparametersResp` + + The hyperparameters used for the fine-tuning job. + + - `BatchSize SupervisedHyperparametersBatchSizeUnionResp` + + Number of examples in each batch. A larger batch size means that model parameters are updated less frequently, but with lower variance. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + + - `LearningRateMultiplier SupervisedHyperparametersLearningRateMultiplierUnionResp` + + Scaling factor for the learning rate. A smaller learning rate may be useful to avoid overfitting. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `float64` + + - `NEpochs SupervisedHyperparametersNEpochsUnionResp` + + The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset. + + - `type Auto string` + + - `const AutoAuto Auto = "auto"` + + - `int64` + +### Fine Tuning Job Event + +- `type FineTuningJobEvent struct{…}` + + Fine-tuning job event object + + - `ID string` + + The object identifier. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the fine-tuning job was created. + + - `Level FineTuningJobEventLevel` + + The log level of the event. + + - `const FineTuningJobEventLevelInfo FineTuningJobEventLevel = "info"` + + - `const FineTuningJobEventLevelWarn FineTuningJobEventLevel = "warn"` + + - `const FineTuningJobEventLevelError FineTuningJobEventLevel = "error"` + + - `Message string` + + The message of the event. + + - `Object FineTuningJobEvent` + + The object type, which is always "fine_tuning.job.event". + + - `const FineTuningJobEventFineTuningJobEvent FineTuningJobEvent = "fine_tuning.job.event"` + + - `Data any` + + The data associated with the event. + + - `Type FineTuningJobEventType` + + The type of event. + + - `const FineTuningJobEventTypeMessage FineTuningJobEventType = "message"` + + - `const FineTuningJobEventTypeMetrics FineTuningJobEventType = "metrics"` + +### Fine Tuning Job Wandb Integration + +- `type FineTuningJobWandbIntegration struct{…}` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + +### Fine Tuning Job Wandb Integration Object + +- `type FineTuningJobWandbIntegrationObject struct{…}` + + - `Type Wandb` + + The type of the integration being enabled for the fine-tuning job + + - `const WandbWandb Wandb = "wandb"` + + - `Wandb FineTuningJobWandbIntegration` + + The settings for your integration with Weights and Biases. This payload specifies the project that + metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags + to your run, and set a default entity (team, username, etc) to be associated with your run. + + - `Project string` + + The name of the project that the new run will be created under. + + - `Entity string` + + The entity to use for the run. This allows you to set the team or username of the WandB user that you would + like associated with the run. If not set, the default entity for the registered WandB API key is used. + + - `Name string` + + A display name to set for the run. If not set, we will use the Job ID as the name. + + - `Tags []string` + + A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some + default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}". + +# Checkpoints + +## List fine-tuning checkpoints + +`client.FineTuning.Jobs.Checkpoints.List(ctx, fineTuningJobID, query) (*CursorPage[FineTuningJobCheckpoint], error)` + +**get** `/fine_tuning/jobs/{fine_tuning_job_id}/checkpoints` + +List fine-tuning checkpoints + +### Parameters + +- `fineTuningJobID string` + +- `query FineTuningJobCheckpointListParams` + + - `After param.Field[string]` + + Identifier for the last checkpoint ID from the previous pagination request. + + - `Limit param.Field[int64]` + + Number of checkpoints to retrieve. + +### Returns + +- `type FineTuningJobCheckpoint struct{…}` + + The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use. + + - `ID string` + + The checkpoint identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the checkpoint was created. + + - `FineTunedModelCheckpoint string` + + The name of the fine-tuned checkpoint model that is created. + + - `FineTuningJobID string` + + The name of the fine-tuning job that this checkpoint was created from. + + - `Metrics FineTuningJobCheckpointMetrics` + + Metrics at the step number during the fine-tuning job. + + - `FullValidLoss float64` + + - `FullValidMeanTokenAccuracy float64` + + - `Step float64` + + - `TrainLoss float64` + + - `TrainMeanTokenAccuracy float64` + + - `ValidLoss float64` + + - `ValidMeanTokenAccuracy float64` + + - `Object FineTuningJobCheckpoint` + + The object type, which is always "fine_tuning.job.checkpoint". + + - `const FineTuningJobCheckpointFineTuningJobCheckpoint FineTuningJobCheckpoint = "fine_tuning.job.checkpoint"` + + - `StepNumber int64` + + The step number that the checkpoint was created at. + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + page, err := client.FineTuning.Jobs.Checkpoints.List( + context.TODO(), + "ft-AF1WoRqd3aJAHsqc9NY7iL8F", + openai.FineTuningJobCheckpointListParams{ + + }, + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", page) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "fine_tuned_model_checkpoint": "fine_tuned_model_checkpoint", + "fine_tuning_job_id": "fine_tuning_job_id", + "metrics": { + "full_valid_loss": 0, + "full_valid_mean_token_accuracy": 0, + "step": 0, + "train_loss": 0, + "train_mean_token_accuracy": 0, + "valid_loss": 0, + "valid_mean_token_accuracy": 0 + }, + "object": "fine_tuning.job.checkpoint", + "step_number": 0 + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Domain Types + +### Fine Tuning Job Checkpoint + +- `type FineTuningJobCheckpoint struct{…}` + + The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use. + + - `ID string` + + The checkpoint identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the checkpoint was created. + + - `FineTunedModelCheckpoint string` + + The name of the fine-tuned checkpoint model that is created. + + - `FineTuningJobID string` + + The name of the fine-tuning job that this checkpoint was created from. + + - `Metrics FineTuningJobCheckpointMetrics` + + Metrics at the step number during the fine-tuning job. + + - `FullValidLoss float64` + + - `FullValidMeanTokenAccuracy float64` + + - `Step float64` + + - `TrainLoss float64` + + - `TrainMeanTokenAccuracy float64` + + - `ValidLoss float64` + + - `ValidMeanTokenAccuracy float64` + + - `Object FineTuningJobCheckpoint` + + The object type, which is always "fine_tuning.job.checkpoint". + + - `const FineTuningJobCheckpointFineTuningJobCheckpoint FineTuningJobCheckpoint = "fine_tuning.job.checkpoint"` + + - `StepNumber int64` + + The step number that the checkpoint was created at. + +# Checkpoints + +# Permissions + +## List checkpoint permissions + +`client.FineTuning.Checkpoints.Permissions.Get(ctx, fineTunedModelCheckpoint, query) (*FineTuningCheckpointPermissionGetResponse, error)` + +**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +List checkpoint permissions + +### Parameters + +- `fineTunedModelCheckpoint string` + +- `query FineTuningCheckpointPermissionGetParams` + + - `After param.Field[string]` + + Identifier for the last permission ID from the previous pagination request. + + - `Limit param.Field[int64]` + + Number of permissions to retrieve. + + - `Order param.Field[FineTuningCheckpointPermissionGetParamsOrder]` + + The order in which to retrieve permissions. + + - `const FineTuningCheckpointPermissionGetParamsOrderAscending FineTuningCheckpointPermissionGetParamsOrder = "ascending"` + + - `const FineTuningCheckpointPermissionGetParamsOrderDescending FineTuningCheckpointPermissionGetParamsOrder = "descending"` + + - `ProjectID param.Field[string]` + + The ID of the project to get permissions for. + +### Returns + +- `type FineTuningCheckpointPermissionGetResponse struct{…}` + + - `Data []FineTuningCheckpointPermissionGetResponseData` + + - `ID string` + + The permission identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the permission was created. + + - `Object CheckpointPermission` + + The object type, which is always "checkpoint.permission". + + - `const CheckpointPermissionCheckpointPermission CheckpointPermission = "checkpoint.permission"` + + - `ProjectID string` + + The project identifier that the permission is for. + + - `HasMore bool` + + - `Object List` + + - `const ListList List = "list"` + + - `FirstID string` + + - `LastID string` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + permission, err := client.FineTuning.Checkpoints.Permissions.Get( + context.TODO(), + "ft-AF1WoRqd3aJAHsqc9NY7iL8F", + openai.FineTuningCheckpointPermissionGetParams{ + + }, + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", permission.FirstID) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## List checkpoint permissions + +`client.FineTuning.Checkpoints.Permissions.List(ctx, fineTunedModelCheckpoint, query) (*ConversationCursorPage[FineTuningCheckpointPermissionListResponse], error)` + +**get** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +List checkpoint permissions + +### Parameters + +- `fineTunedModelCheckpoint string` + +- `query FineTuningCheckpointPermissionListParams` + + - `After param.Field[string]` + + Identifier for the last permission ID from the previous pagination request. + + - `Limit param.Field[int64]` + + Number of permissions to retrieve. + + - `Order param.Field[FineTuningCheckpointPermissionListParamsOrder]` + + The order in which to retrieve permissions. + + - `const FineTuningCheckpointPermissionListParamsOrderAscending FineTuningCheckpointPermissionListParamsOrder = "ascending"` + + - `const FineTuningCheckpointPermissionListParamsOrderDescending FineTuningCheckpointPermissionListParamsOrder = "descending"` + + - `ProjectID param.Field[string]` + + The ID of the project to get permissions for. + +### Returns + +- `type FineTuningCheckpointPermissionListResponse struct{…}` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `ID string` + + The permission identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the permission was created. + + - `Object CheckpointPermission` + + The object type, which is always "checkpoint.permission". + + - `const CheckpointPermissionCheckpointPermission CheckpointPermission = "checkpoint.permission"` + + - `ProjectID string` + + The project identifier that the permission is for. + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + page, err := client.FineTuning.Checkpoints.Permissions.List( + context.TODO(), + "ft-AF1WoRqd3aJAHsqc9NY7iL8F", + openai.FineTuningCheckpointPermissionListParams{ + + }, + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", page) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Create checkpoint permissions + +`client.FineTuning.Checkpoints.Permissions.New(ctx, fineTunedModelCheckpoint, body) (*Page[FineTuningCheckpointPermissionNewResponse], error)` + +**post** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions` + +Create checkpoint permissions + +### Parameters + +- `fineTunedModelCheckpoint string` + +- `body FineTuningCheckpointPermissionNewParams` + + - `ProjectIDs param.Field[[]string]` + + The project identifiers to grant access to. + +### Returns + +- `type FineTuningCheckpointPermissionNewResponse struct{…}` + + The `checkpoint.permission` object represents a permission for a fine-tuned model checkpoint. + + - `ID string` + + The permission identifier, which can be referenced in the API endpoints. + + - `CreatedAt int64` + + The Unix timestamp (in seconds) for when the permission was created. + + - `Object CheckpointPermission` + + The object type, which is always "checkpoint.permission". + + - `const CheckpointPermissionCheckpointPermission CheckpointPermission = "checkpoint.permission"` + + - `ProjectID string` + + The project identifier that the permission is for. + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + page, err := client.FineTuning.Checkpoints.Permissions.New( + context.TODO(), + "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd", + openai.FineTuningCheckpointPermissionNewParams{ + ProjectIDs: []string{"string"}, + }, + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", page) +} +``` + +#### Response + +```json +{ + "data": [ + { + "id": "id", + "created_at": 0, + "object": "checkpoint.permission", + "project_id": "project_id" + } + ], + "has_more": true, + "object": "list", + "first_id": "first_id", + "last_id": "last_id" +} +``` + +## Delete checkpoint permission + +`client.FineTuning.Checkpoints.Permissions.Delete(ctx, fineTunedModelCheckpoint, permissionID) (*FineTuningCheckpointPermissionDeleteResponse, error)` + +**delete** `/fine_tuning/checkpoints/{fine_tuned_model_checkpoint}/permissions/{permission_id}` + +Delete checkpoint permission + +### Parameters + +- `fineTunedModelCheckpoint string` + +- `permissionID string` + +### Returns + +- `type FineTuningCheckpointPermissionDeleteResponse struct{…}` + + - `ID string` + + The ID of the fine-tuned model checkpoint permission that was deleted. + + - `Deleted bool` + + Whether the fine-tuned model checkpoint permission was successfully deleted. + + - `Object CheckpointPermission` + + The object type, which is always "checkpoint.permission". + + - `const CheckpointPermissionCheckpointPermission CheckpointPermission = "checkpoint.permission"` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + permission, err := client.FineTuning.Checkpoints.Permissions.Delete( + context.TODO(), + "ft:gpt-4o-mini-2024-07-18:org:weather:B7R9VjQd", + "cp_zc4Q7MP6XxulcVzj4MZdwsAB", + ) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", permission.ID) +} +``` + +#### Response + +```json +{ + "id": "id", + "deleted": true, + "object": "checkpoint.permission" +} +``` + +# Alpha + +# Graders + +## Run grader + +`client.FineTuning.Alpha.Graders.Run(ctx, body) (*FineTuningAlphaGraderRunResponse, error)` + +**post** `/fine_tuning/alpha/graders/run` + +Run grader + +### Parameters + +- `body FineTuningAlphaGraderRunParams` + + - `Grader param.Field[FineTuningAlphaGraderRunParamsGraderUnion]` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + + - `ModelSample param.Field[string]` + + The model sample to be evaluated. This value will be used to populate + the `sample` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details. + The `output_json` variable will be populated if the model sample is a + valid JSON string. + + - `Item param.Field[any]` + + The dataset item provided to the grader. This will be used to populate + the `item` namespace. See [the guide](https://platform.openai.com/docs/guides/graders) for more details. + +### Returns + +- `type FineTuningAlphaGraderRunResponse struct{…}` + + - `Metadata FineTuningAlphaGraderRunResponseMetadata` + + - `Errors FineTuningAlphaGraderRunResponseMetadataErrors` + + - `FormulaParseError bool` + + - `InvalidVariableError bool` + + - `ModelGraderParseError bool` + + - `ModelGraderRefusalError bool` + + - `ModelGraderServerError bool` + + - `ModelGraderServerErrorDetails string` + + - `OtherError bool` + + - `PythonGraderRuntimeError bool` + + - `PythonGraderRuntimeErrorDetails string` + + - `PythonGraderServerError bool` + + - `PythonGraderServerErrorType string` + + - `SampleParseError bool` + + - `TruncatedObservationError bool` + + - `UnresponsiveRewardError bool` + + - `ExecutionTime float64` + + - `Name string` + + - `SampledModelName string` + + - `Scores map[string, any]` + + - `TokenUsage int64` + + - `Type string` + + - `ModelGraderTokenUsagePerModel map[string, any]` + + - `Reward float64` + + - `SubRewards map[string, any]` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + response, err := client.FineTuning.Alpha.Graders.Run(context.TODO(), openai.FineTuningAlphaGraderRunParams{ + Grader: openai.FineTuningAlphaGraderRunParamsGraderUnion{ + OfStringCheck: &openai.StringCheckGraderParam{ + Input: "input", + Name: "name", + Operation: openai.StringCheckGraderOperationEq, + Reference: "reference", + }, + }, + ModelSample: "model_sample", + }) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", response.Metadata) +} +``` + +#### Response + +```json +{ + "metadata": { + "errors": { + "formula_parse_error": true, + "invalid_variable_error": true, + "model_grader_parse_error": true, + "model_grader_refusal_error": true, + "model_grader_server_error": true, + "model_grader_server_error_details": "model_grader_server_error_details", + "other_error": true, + "python_grader_runtime_error": true, + "python_grader_runtime_error_details": "python_grader_runtime_error_details", + "python_grader_server_error": true, + "python_grader_server_error_type": "python_grader_server_error_type", + "sample_parse_error": true, + "truncated_observation_error": true, + "unresponsive_reward_error": true + }, + "execution_time": 0, + "name": "name", + "sampled_model_name": "sampled_model_name", + "scores": { + "foo": "bar" + }, + "token_usage": 0, + "type": "type" + }, + "model_grader_token_usage_per_model": { + "foo": "bar" + }, + "reward": 0, + "sub_rewards": { + "foo": "bar" + } +} +``` + +## Validate grader + +`client.FineTuning.Alpha.Graders.Validate(ctx, body) (*FineTuningAlphaGraderValidateResponse, error)` + +**post** `/fine_tuning/alpha/graders/validate` + +Validate grader + +### Parameters + +- `body FineTuningAlphaGraderValidateParams` + + - `Grader param.Field[FineTuningAlphaGraderValidateParamsGraderUnion]` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + +### Returns + +- `type FineTuningAlphaGraderValidateResponse struct{…}` + + - `Grader FineTuningAlphaGraderValidateResponseGraderUnion` + + The grader used for the fine-tuning job. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `Input string` + + The input text. This may include template strings. + + - `Name string` + + The name of the grader. + + - `Operation StringCheckGraderOperation` + + The string check operation to perform. One of `eq`, `ne`, `like`, or `ilike`. + + - `const StringCheckGraderOperationEq StringCheckGraderOperation = "eq"` + + - `const StringCheckGraderOperationNe StringCheckGraderOperation = "ne"` + + - `const StringCheckGraderOperationLike StringCheckGraderOperation = "like"` + + - `const StringCheckGraderOperationIlike StringCheckGraderOperation = "ilike"` + + - `Reference string` + + The reference text. This may include template strings. + + - `Type StringCheck` + + The object type, which is always `string_check`. + + - `const StringCheckStringCheck StringCheck = "string_check"` + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `EvaluationMetric TextSimilarityGraderEvaluationMetric` + + The evaluation metric to use. One of `cosine`, `fuzzy_match`, `bleu`, + `gleu`, `meteor`, `rouge_1`, `rouge_2`, `rouge_3`, `rouge_4`, `rouge_5`, + or `rouge_l`. + + - `const TextSimilarityGraderEvaluationMetricCosine TextSimilarityGraderEvaluationMetric = "cosine"` + + - `const TextSimilarityGraderEvaluationMetricFuzzyMatch TextSimilarityGraderEvaluationMetric = "fuzzy_match"` + + - `const TextSimilarityGraderEvaluationMetricBleu TextSimilarityGraderEvaluationMetric = "bleu"` + + - `const TextSimilarityGraderEvaluationMetricGleu TextSimilarityGraderEvaluationMetric = "gleu"` + + - `const TextSimilarityGraderEvaluationMetricMeteor TextSimilarityGraderEvaluationMetric = "meteor"` + + - `const TextSimilarityGraderEvaluationMetricRouge1 TextSimilarityGraderEvaluationMetric = "rouge_1"` + + - `const TextSimilarityGraderEvaluationMetricRouge2 TextSimilarityGraderEvaluationMetric = "rouge_2"` + + - `const TextSimilarityGraderEvaluationMetricRouge3 TextSimilarityGraderEvaluationMetric = "rouge_3"` + + - `const TextSimilarityGraderEvaluationMetricRouge4 TextSimilarityGraderEvaluationMetric = "rouge_4"` + + - `const TextSimilarityGraderEvaluationMetricRouge5 TextSimilarityGraderEvaluationMetric = "rouge_5"` + + - `const TextSimilarityGraderEvaluationMetricRougeL TextSimilarityGraderEvaluationMetric = "rouge_l"` + + - `Input string` + + The text being graded. + + - `Name string` + + The name of the grader. + + - `Reference string` + + The text being graded against. + + - `Type TextSimilarity` + + The type of grader. + + - `const TextSimilarityTextSimilarity TextSimilarity = "text_similarity"` + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `Name string` + + The name of the grader. + + - `Source string` + + The source code of the python script. + + - `Type Python` + + The object type, which is always `python`. + + - `const PythonPython Python = "python"` + + - `ImageTag string` + + The image tag to use for the python script. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `Input []ScoreModelGraderInput` + + The input messages evaluated by the grader. Supports text, output text, input image, and input audio content blocks, and may include template strings. + + - `Content ScoreModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `Text string` + + The text input to the model. + + - `Type InputText` + + The type of the input item. Always `input_text`. + + - `const InputTextInputText InputText = "input_text"` + + - `PromptCacheBreakpoint ResponseInputTextPromptCacheBreakpoint` + + Marks the exact end of a reusable prompt prefix. The breakpoint inherits its TTL from the request's `prompt_cache_options.ttl`; the boundary is not rounded to a token block. + + - `Mode Explicit` + + The breakpoint mode. Always `explicit`. + + - `const ExplicitExplicit Explicit = "explicit"` + + - `type ScoreModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type ScoreModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `InputAudio ResponseInputAudioInputAudio` + + - `Data string` + + Base64-encoded audio data. + + - `Format string` + + The format of the audio data. Currently supported formats are `mp3` and + `wav`. + + - `const ResponseInputAudioInputAudioFormatMP3 ResponseInputAudioInputAudioFormat = "mp3"` + + - `const ResponseInputAudioInputAudioFormatWAV ResponseInputAudioInputAudioFormat = "wav"` + + - `Type InputAudio` + + The type of the input item. Always `input_audio`. + + - `const InputAudioInputAudio InputAudio = "input_audio"` + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type GraderInputOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type GraderInputInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const ScoreModelGraderInputRoleUser ScoreModelGraderInputRole = "user"` + + - `const ScoreModelGraderInputRoleAssistant ScoreModelGraderInputRole = "assistant"` + + - `const ScoreModelGraderInputRoleSystem ScoreModelGraderInputRole = "system"` + + - `const ScoreModelGraderInputRoleDeveloper ScoreModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const ScoreModelGraderInputTypeMessage ScoreModelGraderInputType = "message"` + + - `Model string` + + The model to use for the evaluation. + + - `Name string` + + The name of the grader. + + - `Type ScoreModel` + + The object type, which is always `score_model`. + + - `const ScoreModelScoreModel ScoreModel = "score_model"` + + - `Range []float64` + + The range of the score. Defaults to `[0, 1]`. + + - `SamplingParams ScoreModelGraderSamplingParams` + + The sampling parameters for the model. + + - `MaxCompletionsTokens int64` + + The maximum number of tokens the grader model may generate in its response. + + - `ReasoningEffort ReasoningEffort` + + Constrains effort on reasoning for reasoning models. Currently supported + values are `none`, `minimal`, `low`, `medium`, `high`, `xhigh`, and `max`. + Reducing reasoning effort can result in faster responses and fewer tokens + used on reasoning in a response. Not all reasoning models support every + value. See the + [reasoning guide](https://platform.openai.com/docs/guides/reasoning) + for model-specific support. + + - `const ReasoningEffortNone ReasoningEffort = "none"` + + - `const ReasoningEffortMinimal ReasoningEffort = "minimal"` + + - `const ReasoningEffortLow ReasoningEffort = "low"` + + - `const ReasoningEffortMedium ReasoningEffort = "medium"` + + - `const ReasoningEffortHigh ReasoningEffort = "high"` + + - `const ReasoningEffortXhigh ReasoningEffort = "xhigh"` + + - `const ReasoningEffortMax ReasoningEffort = "max"` + + - `Seed int64` + + A seed value to initialize the randomness, during sampling. + + - `Temperature float64` + + A higher temperature increases randomness in the outputs. + + - `TopP float64` + + An alternative to temperature for nucleus sampling; 1.0 includes all tokens. + + - `type MultiGrader struct{…}` + + A MultiGrader object combines the output of multiple graders to produce a single score. + + - `CalculateOutput string` + + A formula to calculate the output based on grader results. + + - `Graders MultiGraderGradersUnion` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type StringCheckGrader struct{…}` + + A StringCheckGrader object that performs a string comparison between input and reference using a specified operation. + + - `type TextSimilarityGrader struct{…}` + + A TextSimilarityGrader object which grades text based on similarity metrics. + + - `type PythonGrader struct{…}` + + A PythonGrader object that runs a python script on the input. + + - `type ScoreModelGrader struct{…}` + + A ScoreModelGrader object that uses a model to assign a score to the input. + + - `type LabelModelGrader struct{…}` + + A LabelModelGrader object which uses a model to assign labels to each item + in the evaluation. + + - `Input []LabelModelGraderInput` + + - `Content LabelModelGraderInputContentUnion` + + Inputs to the model - can contain template strings. Supports text, output text, input images, and input audio, either as a single item or an array of items. + + - `string` + + - `type ResponseInputText struct{…}` + + A text input to the model. + + - `type LabelModelGraderInputContentOutputText struct{…}` + + A text output from the model. + + - `Text string` + + The text output from the model. + + - `Type OutputText` + + The type of the output text. Always `output_text`. + + - `const OutputTextOutputText OutputText = "output_text"` + + - `type LabelModelGraderInputContentInputImage struct{…}` + + An image input block used within EvalItem content arrays. + + - `ImageURL string` + + The URL of the image input. + + - `Type InputImage` + + The type of the image input. Always `input_image`. + + - `const InputImageInputImage InputImage = "input_image"` + + - `Detail string` + + The detail level of the image to be sent to the model. One of `high`, `low`, or `auto`. Defaults to `auto`. + + - `type ResponseInputAudio struct{…}` + + An audio input to the model. + + - `type GraderInputs []GraderInputUnion` + + A list of inputs, each of which may be either an input text, output text, input + image, or input audio object. + + - `Role string` + + The role of the message input. One of `user`, `assistant`, `system`, or + `developer`. + + - `const LabelModelGraderInputRoleUser LabelModelGraderInputRole = "user"` + + - `const LabelModelGraderInputRoleAssistant LabelModelGraderInputRole = "assistant"` + + - `const LabelModelGraderInputRoleSystem LabelModelGraderInputRole = "system"` + + - `const LabelModelGraderInputRoleDeveloper LabelModelGraderInputRole = "developer"` + + - `Type string` + + The type of the message input. Always `message`. + + - `const LabelModelGraderInputTypeMessage LabelModelGraderInputType = "message"` + + - `Labels []string` + + The labels to assign to each item in the evaluation. + + - `Model string` + + The model to use for the evaluation. Must support structured outputs. + + - `Name string` + + The name of the grader. + + - `PassingLabels []string` + + The labels that indicate a passing result. Must be a subset of labels. + + - `Type LabelModel` + + The object type, which is always `label_model`. + + - `const LabelModelLabelModel LabelModel = "label_model"` + + - `Name string` + + The name of the grader. + + - `Type Multi` + + The object type, which is always `multi`. + + - `const MultiMulti Multi = "multi"` + +### Example + +```go +package main + +import ( + "context" + "fmt" + + "github.com/openai/openai-go" + "github.com/openai/openai-go/option" +) + +func main() { + client := openai.NewClient( + option.WithAPIKey("My API Key"), + ) + response, err := client.FineTuning.Alpha.Graders.Validate(context.TODO(), openai.FineTuningAlphaGraderValidateParams{ + Grader: openai.FineTuningAlphaGraderValidateParamsGraderUnion{ + OfStringCheckGrader: &openai.StringCheckGraderParam{ + Input: "input", + Name: "name", + Operation: openai.StringCheckGraderOperationEq, + Reference: "reference", + }, + }, + }) + if err != nil { + panic(err.Error()) + } + fmt.Printf("%+v\n", response.Grader) +} +``` + +#### Response + +```json +{ + "grader": { + "input": "input", + "name": "name", + "operation": "eq", + "reference": "reference", + "type": "string_check" + } +} +```