Overview

This model, tsavage68/chat_200STEPS_1e6_01beta, is a 7 billion parameter language model derived from the meta-llama/Llama-2-7b-chat-hf architecture. It has undergone a fine-tuning process, though the specific dataset used for this fine-tuning is not detailed in the model card. The training involved 200 steps with a learning rate of 1e-06 and a total batch size of 8, utilizing an Adam optimizer.

Training Results

During its 200-step training, the model achieved a final validation loss of 0.6840. Key reward metrics from the evaluation set include a chosen reward of -0.0632 and a rejected reward of -0.0877, with a reward accuracy of 0.4637. The training procedure used Transformers 4.37.2 and Pytorch 2.0.0+cu117.

Intended Uses

Given its base as a chat-hf model, this fine-tuned version is likely intended for conversational AI applications. However, specific use cases and limitations are not explicitly defined in the provided model information.