Overview

This model, mmlu_same_f_llama2, is a fine-tuned variant of the Meta Llama-2-7b-chat-hf architecture. It features 7 billion parameters and was developed by Vivian12300. The fine-tuning process involved a specific "generator dataset," suggesting an optimization for particular data generation or transformation tasks.

Training Details

The model was trained using the following key hyperparameters:

• Learning Rate: 5e-05
• Batch Size: 1 (train), 2 (eval)
• Gradient Accumulation Steps: 16 (resulting in a total effective batch size of 16)
• Optimizer: Adam with standard betas and epsilon
• LR Scheduler: Linear
• Epochs: 30

Key Characteristics

• Base Model: Llama-2-7b-chat-hf
• Parameter Count: 7 billion
• Fine-tuning Focus: Generator dataset, implying specialized output generation.

Limitations

As per the provided documentation, specific intended uses, limitations, and detailed training/evaluation data require further information. Users should exercise caution and conduct thorough testing for any specific application.