Model Overview

The CharlesLi/llama_3_alpaca_helpful model is an 8 billion parameter language model, fine-tuned from the robust Meta Llama-3.1-8B-Instruct base model. It was trained with a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating more extensive responses.

Training Details

The model underwent a fine-tuning process using specific hyperparameters, including a learning rate of 0.0002, a total batch size of 16, and an Adam optimizer. Training consisted of 30 steps, resulting in a final validation loss of 0.8488. The training utilized PEFT 0.12.0, Transformers 4.44.2, and Pytorch 2.4.1+cu121.

Key Characteristics

• Base Model: Meta Llama-3.1-8B-Instruct
• Parameter Count: 8 Billion
• Context Length: 32768 tokens
• Training Objective: Achieved a validation loss of 0.8488, indicating effective fine-tuning.

Intended Use Cases

This model is designed for applications requiring a helpful assistant, leveraging the strong foundational capabilities of the Llama 3.1 series. Its fine-tuning aims to enhance its performance in generating useful and relevant responses for a variety of prompts.