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Training

The Training section is where you fine-tune your AI assistant using the data prepared in the Data Pre-Processing phase. This process customizes the assistant to better understand your application's context, structure, and user queries.

Training involves providing a dataset of Questions and Answers (Q&As) and augmenting it with additional variations to enhance the model’s understanding.

Training Form

Training Form Overview​

The training form provides options for configuring and initiating the training process. Below are the key fields and their purposes:

New Training Data Progress Bar​

  • Indicates whether there are enough new (unfrozen) Q&As available for training the assistant.
  • Ensure that you have sufficient new data to meet the required minimum.

Training Data​

  • Options:
    • New Data Only: Uses only new (unfrozen) Q&As for training.
    • All Data: Includes both new (unfrozen) and previously frozen Q&As in the training dataset.

Progress Bar​

  • Displays the sufficiency of the selected dataset to meet the recommended minimum for fine-tuning.

Advanced Options​

Click the Advanced Options dropdown to customize the training process further:

  • Base Model: Select the base model for training. By default, the last trained model is used. If you want to train from scratch, you can choose "GPT-4o-mini".

  • Epochs: Specify the number of epochs (training cycles). Recommended default is 3.

  • Batch Size: The number of examples processed in each batch. Recommended default is 1.

  • Learning Rate Multiplier: A scaling factor for the learning rate, which influences how the model updates during training. Recommended default is 3.0.

    Advanced Options

Estimated Training Cost​

  • Training costs are displayed in credits and depend on the volume of data augmented for training.
  • Actual costs may vary up to 2x the estimate due to the additional augmented data generated by the system. However, the actual cost is typically close to or less than the estimate.

Start Training​

Submitting Training​

  1. Once you’ve configured the form, click the Start Training button.

  2. A confirmation modal will appear, summarizing the selected options. Confirm to proceed.

    Confirm Training Modal

What Happens During Training?​

  1. Freezing Knowledge:

    • Once training begins, all Q&As used in the process are frozen to prevent edits.
    • This ensures consistency in training and avoids conflicts caused by training with different answers for the same question.
    • Frozen knowledge can be unfrozen at any time in the Data Pre-Processing section.

  2. Queueing Data for Training:

    • The selected dataset is augmented with AI to generate variations of questions and answers.
    • Augmented data and user-provided data are split into training and validation sets.
    • The prepared data is uploaded for fine-tuning the assistant.

Training Timeline​

Training Timeline

The Training Timeline panel on the right provides a live update on the training progress:

  • Queued: Training data is waiting to be processed.
  • Training: The model is currently being fine-tuned.
  • Completed: Training is finished, and the model is ready for use.

Once the training reaches the Completed state:

  • The Model ID is displayed and can be copied for reference.
  • Credits are deducted from the organization’s credit balance based on the final training cost.

Best Practices for Training​

  • Sufficient Data: Ensure you have enough Q&As to meet the recommended minimum.

Next Steps​

After training is queued, you can skip to the Evaluation section to manage test cases to evaluate your assistant's responses.