Hyeongwon/P19-split4-prob-6x-bs128-lr2e5-zero3-ep3
The Hyeongwon/P19-split4-prob-6x-bs128-lr2e5-zero3-ep3 model is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base. Trained using TRL (Transformer Reinforcement Learning) with SFT (Supervised Fine-Tuning), this model is designed for text generation tasks. It leverages a 32K context length, making it suitable for processing longer inputs and generating coherent, extended responses.
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Model Overview
Hyeongwon/P19-split4-prob-6x-bs128-lr2e5-zero3-ep3 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. This model was developed using the TRL (Transformer Reinforcement Learning) library, specifically employing Supervised Fine-Tuning (SFT) as its training procedure.
Key Capabilities
- Text Generation: Optimized for generating coherent and contextually relevant text based on user prompts.
- Extended Context Handling: Benefits from a 32,768-token context window, allowing it to process and generate longer sequences of text.
- Fine-tuned Performance: Built upon a robust base model and further refined through SFT for improved task-specific performance.
Training Details
The model's training process utilized TRL version 0.25.1, Transformers 4.57.3, Pytorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2. The training run details are available for visualization on Weights & Biases.
Good For
- Conversational AI: Generating responses in interactive dialogue systems.
- Creative Writing: Assisting with generating stories, poems, or other creative content.
- Question Answering: Providing detailed answers to open-ended questions, leveraging its extended context capabilities.