hpcaitech
chatgpt
📚 The doc issue
Hi,
The first step of chatgpt is to finetune a SFT. I would like to know how to do this? Does the code already implemented here ? TKS!
Yes, the code for finetuning a GPT-based model is already implemented in the ChatGPT system. However, the details of how to do this depend on the specific task and dataset that you want to use for finetuning.
In general, the process of finetuning a GPT-based model involves the following steps:
Prepare the dataset: Collect and preprocess a dataset that is relevant to your task. This typically involves cleaning and formatting the data, and splitting it into training, validation, and test sets.
Choose a pre-trained model: Select a pre-trained GPT-based model that is appropriate for your task. The ChatGPT system uses the GPT-2 and GPT-3 models from OpenAI.
Initialize the model: Initialize the pre-trained model with the appropriate configuration and load the weights from the pre-trained checkpoint.
Modify the model: Modify the pre-trained model to suit your specific task. This usually involves adding task-specific layers or changing the output layer.
Train the model: Train the modified model on the training dataset using backpropagation and gradient descent. This involves iterating over the training data multiple times, adjusting the model weights after each iteration to minimize the loss function.
Evaluate the model: Evaluate the trained model on the validation and test datasets to assess its performance.
Deploy the model: Deploy the trained model in a production environment to make predictions on new data.
The ChatGPT system uses the PyTorch library to implement the GPT-based models and the training process. The code for finetuning a GPT-based model can be found in the train.py and run_generation.py scripts. You can use these scripts as a starting point for finetuning your own GPT-based model.
