Overview
Hyeongwon/PS_prob_seed45_Qwen3-4B-Base_0322-01 is a 4 billion parameter language model that has been fine-tuned from the base model, Hyeongwon/Qwen3-4B-Base. The fine-tuning process utilized Supervised Fine-Tuning (SFT) and was conducted using the TRL (Transformer Reinforcement Learning) library, specifically version 0.25.1. This model is built upon a robust framework, leveraging Transformers 4.57.3 and Pytorch 2.6.0.
Key Capabilities
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
- Fine-tuned Performance: Benefits from SFT, which typically enhances the model's ability to follow instructions and produce more aligned outputs compared to its base model.
- Extended Context Window: Features a 32,768 token context length, allowing it to process and generate longer sequences of text, maintaining context over extended conversations or documents.
Training Details
The model's training procedure involved Supervised Fine-Tuning (SFT). The development environment included TRL 0.25.1, Transformers 4.57.3, Pytorch 2.6.0, Datasets 3.6.0, and Tokenizers 0.22.2. Further details on the training run can be visualized via Weights & Biases.
Good For
- General text generation tasks requiring a moderately sized model.
- Applications where a longer context window is beneficial for maintaining conversational flow or understanding complex documents.
- Developers looking for a fine-tuned Qwen3-4B variant for various NLP applications.