kykim0/llama3-8b-ultrachat-sft
kykim0/llama3-8b-ultrachat-sft is an 8 billion parameter language model fine-tuned from Meta-Llama-3-8B by kykim0. This model was specifically trained on the HuggingFaceH4/ultrachat_200k dataset, aiming to enhance its conversational capabilities. It achieved a validation loss of 1.0405 during training, indicating its specialization in chat-based interactions.
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Overview
kykim0/llama3-8b-ultrachat-sft is an 8 billion parameter language model derived from meta-llama/Meta-Llama-3-8B. This model has undergone supervised fine-tuning (SFT) using the HuggingFaceH4/ultrachat_200k dataset, which is designed to improve its performance in conversational and instruction-following scenarios.
Key Capabilities
- Enhanced Chat Performance: Fine-tuned on a large-scale ultrachat dataset, making it suitable for dialogue systems and interactive applications.
- Llama 3 Base: Benefits from the robust architecture and pre-training of the Meta-Llama-3-8B model.
Training Details
The model was trained with a learning rate of 2e-05 over 2 epochs, utilizing a total batch size of 128 across 8 GPUs. It achieved a final validation loss of 1.0405, indicating effective adaptation to the ultrachat dataset.
Good for
- Developing chatbots and conversational AI agents.
- Instruction-following tasks where clear and coherent responses are crucial.
- Applications requiring a compact yet capable language model for interactive use cases.