W-61/llama3-hh-helpful-qt045-b0p05-20260429-085449
W-61/llama3-hh-helpful-qt045-b0p05-20260429-085449 is an 8 billion parameter causal language model, fine-tuned by W-61 from a Llama 3 base. This model specializes in helpfulness, having been fine-tuned on the Anthropic/hh-rlhf dataset. It is designed for applications requiring robust and helpful conversational AI responses.
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Overview
This model, W-61/llama3-hh-helpful-qt045-b0p05-20260429-085449, is an 8 billion parameter Llama 3-based language model. It has been specifically fine-tuned by W-61 using the Anthropic/hh-rlhf dataset, which focuses on generating helpful and harmless responses. This fine-tuning process aims to enhance the model's ability to provide constructive and relevant information in conversational contexts.
Training Details
The model underwent a single epoch of training with a learning rate of 5e-07 and a total training batch size of 64 across 4 GPUs. The training utilized the AdamW_TORCH optimizer and a cosine learning rate scheduler with a 0.1 warmup ratio. The development environment included Transformers 4.51.0, Pytorch 2.3.1+cu121, Datasets 2.21.0, and Tokenizers 0.21.4.
Key Capabilities
- Enhanced Helpfulness: Optimized for generating responses that are directly useful and informative.
- Conversational AI: Suited for dialogue systems where helpfulness is a primary objective.
Good For
- Applications requiring models to provide helpful and constructive answers.
- Building chatbots or virtual assistants focused on user support and information retrieval.