tsavage68/chat_200STEPS_1e6_01beta
The tsavage68/chat_200STEPS_1e6_01beta is a 7 billion parameter language model, fine-tuned from meta-llama/Llama-2-7b-chat-hf. This model was trained for 200 steps with a learning rate of 1e-06, achieving a validation loss of 0.6840. It is intended for chat-based applications, building upon the Llama 2 architecture.
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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.