# JobMetadata
## Properties
Name | Type | Description | Notes
------------ | ------------- | ------------- | -------------
**training_steps** | Option<**i32**> | The number of training steps to perform. A training step refers to a single update of the model weights during the fine-tuning process. This update is typically calculated using a batch of samples from the training dataset. | [optional]
**train_tokens_per_step** | Option<**i32**> | The number of tokens consumed by one training step. | [optional]
**data_tokens** | Option<**i32**> | The total number of tokens in the training dataset. | [optional]
**train_tokens** | Option<**i32**> | The total number of tokens used during the fine-tuning process. | [optional]
**epochs** | Option<**f32**> | The number of complete passes through the entire training dataset. | [optional]
**expected_duration_seconds** | Option<**i32**> | The approximated time (in seconds) for the fine-tuning process to complete. | [optional]
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