Model Overview

This model, Hyeongwon/P2-split2_bs512_epoch10_2e-5_prob_Qwen3-4B-Base_0320-01, is a 4 billion parameter language model developed by Hyeongwon. It is a fine-tuned version of the base Qwen3-4B-Base model, specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework.

Key Capabilities

• Text Generation: The model is capable of generating coherent and contextually relevant text based on given prompts, as demonstrated by its ability to answer open-ended questions.
• Fine-tuned Performance: Leveraging SFT, this model is optimized for specific text generation tasks, building upon the foundational capabilities of the Qwen3-4B-Base architecture.

Training Details

The model's training utilized the TRL (Transformer Reinforcement Learning) library, with specific framework versions including TRL 0.25.1, Transformers 4.57.3, Pytorch 2.6.0, Datasets 3.6.0, and Tokenizers 0.22.2. The training process can be further visualized via its Weights & Biases run.

Good For

• General Text Generation: Suitable for applications requiring the generation of human-like text responses.
• Question Answering: Particularly effective for generating answers to complex or open-ended questions, as shown in its quick start example.