ChuGyouk/35 is a 4 billion parameter language model, fine-tuned from ChuGyouk/Qwen3-4B-Base-AGUINAS-0p5k. This model was specifically trained using TRL on the ChuGyouk/0120FINAL-SemEval24Task5 dataset, making it suitable for tasks related to the SemEval 2024 Task 5 challenge. It is designed for text generation and understanding within its specialized domain.
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Overview
ChuGyouk/35 is a 4 billion parameter language model developed by ChuGyouk. It is a fine-tuned version of the ChuGyouk/Qwen3-4B-Base-AGUINAS-0p5k base model, specifically adapted through Supervised Fine-Tuning (SFT) using the TRL framework. The training utilized the ChuGyouk/0120FINAL-SemEval24Task5 dataset, indicating its specialization for tasks related to the SemEval 2024 Task 5.
Key Capabilities
- Specialized Text Generation: Fine-tuned on a specific dataset, suggesting proficiency in generating text relevant to the SemEval 2024 Task 5 domain.
- TRL Framework: Developed using the TRL library, which is often associated with reinforcement learning from human feedback (RLHF) or similar fine-tuning approaches, though this model specifically used SFT.
Training Details
The model was trained with the following framework versions:
- TRL: 0.24.0
- Transformers: 4.57.3
- Pytorch: 2.9.1
- Datasets: 4.3.0
- Tokenizers: 0.22.1
Good For
- Researchers and developers working on tasks related to the SemEval 2024 Task 5.
- Applications requiring text generation or understanding within the specific domain covered by the
ChuGyouk/0120FINAL-SemEval24Task5dataset.