Hyeongwon/P19-split3-prob-9x-bs512-lr4e5-zero3-ep3
Hyeongwon/P19-split3-prob-9x-bs512-lr4e5-zero3-ep3 is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base. Trained using TRL with SFT, it features a 32768 token context length. This model is optimized for general text generation tasks, leveraging its fine-tuned capabilities for diverse applications.
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Model Overview
Hyeongwon/P19-split3-prob-9x-bs512-lr4e5-zero3-ep3 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. It was developed using the TRL library and trained with Supervised Fine-Tuning (SFT) techniques. The model supports a substantial context length of 32768 tokens, making it suitable for processing longer inputs and generating coherent, extended responses.
Key Capabilities
- General Text Generation: Capable of generating human-like text based on given prompts.
- Fine-tuned Performance: Benefits from specific fine-tuning to enhance its performance beyond the base model.
- Extended Context Window: Processes and understands information within a 32768 token context, allowing for more complex and detailed interactions.
Training Details
The model's training involved SFT, utilizing specific framework versions including TRL 0.25.1, Transformers 4.57.3, Pytorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2. This configuration indicates a focus on leveraging recent advancements in transformer reinforcement learning and fine-tuning methodologies.
Good For
- Developers seeking a 4B parameter model with a large context window for various text generation tasks.
- Applications requiring a fine-tuned model for improved performance over a base Qwen3-4B architecture.