W-61/llama-3-8b-base-sft-hh-helpful-4xh200
W-61/llama-3-8b-base-sft-hh-helpful-4xh200 is an 8 billion parameter language model fine-tuned from Meta-Llama-3-8B. This model has been specifically fine-tuned on the Anthropic/hh-rlhf dataset, aiming to enhance helpfulness and reduce harmfulness. It is intended for applications requiring a helpful and safe conversational AI, building upon the base capabilities of Llama 3.
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Model Overview
W-61/llama-3-8b-base-sft-hh-helpful-4xh200 is an 8 billion parameter language model derived from meta-llama/Meta-Llama-3-8B. This version has undergone supervised fine-tuning (SFT) using the Anthropic/hh-rlhf dataset, which is designed to improve model helpfulness and align with human preferences, particularly in avoiding harmful outputs.
Key Characteristics
- Base Model: Meta-Llama-3-8B, providing a strong foundation for general language understanding and generation.
- Fine-tuning Objective: Enhanced helpfulness and reduced harmfulness through training on the Anthropic/hh-rlhf dataset.
- Training Details: Trained for 1 epoch with a learning rate of 2e-05, using a total batch size of 64 across 4 GPUs. The training achieved a validation loss of 1.1934.
Intended Use Cases
This model is suitable for applications where a helpful, safe, and instruction-following language model is critical. Potential uses include:
- Conversational AI: Developing chatbots or virtual assistants that provide helpful and non-toxic responses.
- Content Generation: Creating text that adheres to safety guidelines and offers constructive information.
- Instruction Following: Executing user commands in a helpful and aligned manner.
Further details on specific intended uses and limitations are pending from the model developer.