Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0501-bs64-epoch6
Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0501-bs64-epoch6 is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for text generation tasks, specifically for providing direct answers to questions. Its base architecture and fine-tuning focus make it suitable for conversational AI applications requiring concise responses.
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Model Overview
Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0501-bs64-epoch6 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. This model has been specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework (version 0.25.1).
Key Capabilities
- Direct Answering: The model is fine-tuned to provide concise and direct answers, making it suitable for question-answering scenarios.
- Text Generation: Capable of generating coherent text based on user prompts.
- Base Model: Built upon the Qwen3-4B-Base, inheriting its foundational language understanding capabilities.
Training Details
The model underwent Supervised Fine-Tuning (SFT) using the TRL library. The training process utilized Transformers 4.57.3, Pytorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2. Further details on the training run can be visualized via Weights & Biases.
Use Cases
This model is particularly well-suited for applications where a direct and focused answer to a user's question is desired, rather than open-ended conversational responses. It can be integrated into chatbots, virtual assistants, or any system requiring specific information extraction and generation.