Request body which must comply to the following JSON Schema:
{
"required" : [ "model", "training_file" ],
"type" : "object",
"properties" : {
"model" : {
"description" : "The name of the model to fine-tune. You can select one of the\n[supported models](/docs/guides/fine-tuning/what-models-can-be-fine-tuned).\n",
"example" : "gpt-3.5-turbo",
"anyOf" : [ {
"type" : "string"
}, {
"type" : "string",
"enum" : [ "babbage-002", "davinci-002", "gpt-3.5-turbo" ]
} ],
"x-oaiTypeLabel" : "string"
},
"training_file" : {
"type" : "string",
"description" : "The ID of an uploaded file that contains training data.\n\nSee [upload file](/docs/api-reference/files/upload) for how to upload a file.\n\nYour dataset must be formatted as a JSONL file. Additionally, you must upload your file with the purpose `fine-tune`.\n\nSee the [fine-tuning guide](/docs/guides/fine-tuning) for more details.\n",
"example" : "file-abc123"
},
"hyperparameters" : {
"type" : "object",
"properties" : {
"batch_size" : {
"description" : "Number of examples in each batch. A larger batch size means that model parameters\nare updated less frequently, but with lower variance.\n",
"oneOf" : [ {
"type" : "string",
"enum" : [ "auto" ]
}, {
"maximum" : 256,
"minimum" : 1,
"type" : "integer"
} ],
"default" : "auto"
},
"learning_rate_multiplier" : {
"description" : "Scaling factor for the learning rate. A smaller learning rate may be useful to avoid\noverfitting.\n",
"oneOf" : [ {
"type" : "string",
"enum" : [ "auto" ]
}, {
"minimum" : 0,
"exclusiveMinimum" : true,
"type" : "number"
} ],
"default" : "auto"
},
"n_epochs" : {
"description" : "The number of epochs to train the model for. An epoch refers to one full cycle\nthrough the training dataset.\n",
"oneOf" : [ {
"type" : "string",
"enum" : [ "auto" ]
}, {
"maximum" : 50,
"minimum" : 1,
"type" : "integer"
} ],
"default" : "auto"
}
},
"description" : "The hyperparameters used for the fine-tuning job."
},
"suffix" : {
"maxLength" : 40,
"minLength" : 1,
"type" : "string",
"description" : "A string of up to 18 characters that will be added to your fine-tuned model name.\n\nFor example, a `suffix` of \"custom-model-name\" would produce a model name like `ft:gpt-3.5-turbo:openai:custom-model-name:7p4lURel`.\n",
"nullable" : true
},
"validation_file" : {
"type" : "string",
"description" : "The ID of an uploaded file that contains validation data.\n\nIf you provide this file, the data is used to generate validation\nmetrics periodically during fine-tuning. These metrics can be viewed in\nthe fine-tuning results file.\nThe same data should not be present in both train and validation files.\n\nYour dataset must be formatted as a JSONL file. You must upload your file with the purpose `fine-tune`.\n\nSee the [fine-tuning guide](/docs/guides/fine-tuning) for more details.\n",
"nullable" : true,
"example" : "file-abc123"
}
}
}
