Model Overview

This model, llama_2_sky_safe_o1_llama_3_70B_reflect_4000_1000_full, is a fine-tuned variant of Meta's Llama-2-7b-chat-hf (7 billion parameters). It was developed by CharlesLi through a single-epoch training process on a specialized generator dataset.

Training Details

The fine-tuning utilized the following key hyperparameters:

• Learning Rate: 2e-05
• Batch Size: 4 (train and eval)
• Gradient Accumulation: 2 steps, resulting in a total effective batch size of 32
• Optimizer: Adam with standard betas and epsilon
• Scheduler: Cosine with a 0.1 warmup ratio

During training, the model achieved a validation loss of 0.7594 after 200 steps. The training was conducted using Transformers 4.44.2, Pytorch 2.4.1+cu121, Datasets 3.0.0, and Tokenizers 0.19.1.

Potential Use Cases

Given its foundation on Llama-2-7b-chat-hf and fine-tuning on a generator dataset, this model is likely suitable for applications that benefit from:

• Text generation tasks where the generator dataset's characteristics are relevant.
• Chatbot or conversational AI systems requiring a Llama-2 base with specific behavioral adjustments.
• Further experimentation or fine-tuning for domain-specific applications building upon its current training.