Model Overview

This model, llama_2_rlhf_safe_llama_3_70B_default_500_full, is a fine-tuned variant of the meta-llama/Llama-2-7b-chat-hf base model. It features 7 billion parameters and was trained with a context length of 4096 tokens. The fine-tuning process involved a specific generator dataset, resulting in an evaluation loss of 0.9015.

Training Details

The model was trained using the following key hyperparameters:

• Learning Rate: 2e-05
• Batch Sizes: train_batch_size of 4, eval_batch_size of 4
• Optimizer: Adam with default betas and epsilon
• Scheduler: Cosine learning rate scheduler with a 0.1 warmup ratio
• Epochs: 1

Key Characteristics

• Base Model: Fine-tuned from meta-llama/Llama-2-7b-chat-hf.
• Parameter Count: 7 billion parameters.
• Evaluation Performance: Achieved a loss of 0.9015 on its evaluation set, indicating its performance on the specific fine-tuning task.

Intended Use Cases

This model is suitable for applications that can leverage a Llama-2-7b-chat-hf derivative, particularly where its specific fine-tuning on a generator dataset aligns with the desired output characteristics. Developers should consider its base architecture and fine-tuning focus when integrating it into their projects.