Hyeongwon/P2-split5_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5
Hyeongwon/P2-split5_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5 is a 4 billion parameter language model fine-tuned by Hyeongwon from the Qwen3-4B-Base architecture. This model has been specifically trained using Supervised Fine-Tuning (SFT) with TRL, focusing on generating direct answers. It is designed for tasks requiring concise and relevant responses, leveraging its 32768 token context length for processing detailed prompts. Its fine-tuned nature makes it suitable for applications where direct answer generation is critical.
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Model Overview
Hyeongwon/P2-split5_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5 is a 4 billion parameter language model developed by Hyeongwon. It is a fine-tuned variant of the Qwen3-4B-Base model, specifically optimized for generating direct answers to given prompts. The model was trained using Supervised Fine-Tuning (SFT) with the TRL library, indicating a focus on improving response quality for specific answer-generation tasks.
Key Capabilities
- Direct Answer Generation: Specialized in providing concise and relevant answers to questions.
- Base Model Fine-tuning: Built upon the robust Qwen3-4B-Base architecture, inheriting its foundational language understanding.
- TRL Framework: Utilizes the Transformer Reinforcement Learning (TRL) library for its fine-tuning process, suggesting an emphasis on performance optimization for its intended use case.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) procedure. The training leveraged specific versions of popular machine learning frameworks, including TRL 0.25.1, Transformers 4.57.3, PyTorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2. This fine-tuning process aims to enhance its ability to extract and formulate direct answers from input.
Use Cases
This model is particularly well-suited for applications where the primary requirement is to generate straightforward and accurate answers, such as:
- Question-answering systems.
- Information extraction requiring direct responses.
- Chatbots designed for factual queries.