Model Overview

This model, llama_2_sky_safe_o1_4o_reflect_4000_100_full, is a 7 billion parameter language model fine-tuned by CharlesLi. It is based on the meta-llama/Llama-2-7b-chat-hf architecture, indicating its foundation in a robust, general-purpose conversational model.

Training Details

The model underwent a single epoch of training with a learning rate of 2e-05, utilizing an Adam optimizer. Key training hyperparameters include a train_batch_size of 4, gradient_accumulation_steps of 2, and a total_train_batch_size of 32. During training, it achieved a validation loss of 0.5510.

Key Characteristics

• Base Model: Fine-tuned from meta-llama/Llama-2-7b-chat-hf.
• Parameter Count: 7 billion parameters.
• Context Length: 4096 tokens (inherited from Llama-2 base).
• Training Frameworks: Transformers 4.44.2, Pytorch 2.4.1+cu121, Datasets 3.0.0, Tokenizers 0.19.1.

Intended Uses & Limitations

Specific intended uses and limitations are not detailed in the provided information. Given its Llama-2-chat base, it is likely suitable for various conversational AI tasks, text generation, and understanding. However, without further information on the fine-tuning dataset or specific optimizations, its unique strengths or ideal applications remain to be fully defined. Users should conduct further evaluation for specific use cases.