Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5
Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5 is a 4 billion parameter language model developed by Hyeongwon, fine-tuned from Hyeongwon/Qwen3-4B-Base. This model was trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is specifically designed to generate direct answers, making it suitable for question-answering tasks where concise responses are preferred. The model leverages a 32K token context length for processing longer inputs.
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Model Overview
Hyeongwon/P2-split3_only_answer_Qwen3-4B-Base_0505-bs64-epoch6-lr1e5 is a 4 billion parameter language model, fine-tuned by Hyeongwon from its base model, Hyeongwon/Qwen3-4B-Base. This model has been specifically trained using Supervised Fine-Tuning (SFT) via the TRL library, focusing on generating direct answers.
Key Capabilities
- Direct Answer Generation: Optimized to provide concise and relevant answers to user queries, making it suitable for specific question-answering scenarios.
- Base Model Fine-tuning: Built upon the Qwen3-4B-Base architecture, inheriting its foundational language understanding capabilities.
- Context Length: Supports a context window of 32,768 tokens, allowing it to process and understand longer prompts or conversational histories.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process. The training utilized specific framework versions:
- TRL: 0.25.1
- Transformers: 4.57.3
- Pytorch: 2.9.1
- Datasets: 3.6.0
- Tokenizers: 0.22.2
Intended Use Cases
This model is particularly well-suited for applications requiring direct and focused responses, such as:
- Automated customer support systems for answering specific questions.
- Information retrieval where precise answers are needed.
- Educational tools for generating factual responses.