Hyeongwon/P12-split4-one-sided-bs64-lr2e5-zero3-ep3
Hyeongwon/P12-split4-one-sided-bs64-lr2e5-zero3-ep3 is a 4 billion parameter language model fine-tuned from Hyeongwon/Qwen3-4B-Base. Trained using TRL, this model is optimized for text generation tasks. It features a 32768 token context length, making it suitable for applications requiring processing of longer inputs and generating coherent, extended responses.
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Model Overview
Hyeongwon/P12-split4-one-sided-bs64-lr2e5-zero3-ep3 is a 4 billion parameter language model derived from the Hyeongwon/Qwen3-4B-Base architecture. This model has undergone supervised fine-tuning (SFT) using the TRL (Transformer Reinforcement Learning) library, indicating a focus on improving its performance for specific generative tasks.
Key Capabilities
- Text Generation: The model is primarily designed for generating human-like text based on given prompts.
- Extended Context: With a context length of 32768 tokens, it can process and generate responses for longer inputs, maintaining coherence over extended conversations or documents.
- Fine-tuned Performance: The SFT training process aims to enhance its ability to follow instructions and produce relevant outputs for various text generation applications.
Training Details
The model was fine-tuned using TRL version 0.25.1, with Transformers 4.57.3, Pytorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2. The training process can be visualized via Weights & Biases, as indicated in the original model card.
When to Use This Model
This model is suitable for developers looking for a 4B parameter model capable of:
- Generating creative or conversational text.
- Handling prompts that require a deep understanding of context due to its large context window.
- Applications where a fine-tuned base model offers improved instruction following compared to its base counterpart.