Hyeongwon/P19-split5-prob-3x-bs64-lr2e5-zero3-ep3
The Hyeongwon/P19-split5-prob-3x-bs64-lr2e5-zero3-ep3 model is a 4 billion parameter language model, fine-tuned from Hyeongwon/Qwen3-4B-Base using the TRL library. This model is designed for text generation tasks, particularly for conversational or question-answering scenarios, leveraging its base Qwen3 architecture. It was trained with Supervised Fine-Tuning (SFT) to enhance its generative capabilities for diverse prompts.
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Model Overview
Hyeongwon/P19-split5-prob-3x-bs64-lr2e5-zero3-ep3 is a 4 billion parameter language model, fine-tuned from the Hyeongwon/Qwen3-4B-Base architecture. This model leverages the capabilities of the Qwen3 family, known for its strong performance in various language understanding and generation tasks.
Key Capabilities
- Text Generation: Optimized for generating coherent and contextually relevant text based on user prompts.
- Instruction Following: Fine-tuned using Supervised Fine-Tuning (SFT) with the TRL library, suggesting improved ability to follow instructions and generate targeted responses.
- Conversational AI: Suitable for applications requiring interactive text generation, such as chatbots or virtual assistants, as demonstrated by the example prompt.
Training Details
The model underwent a Supervised Fine-Tuning (SFT) process. The training run can be visualized on Weights & Biases, providing insights into its training progression and metrics. Key framework versions used include TRL 0.25.1, Transformers 4.57.3, PyTorch 2.9.1, Datasets 3.6.0, and Tokenizers 0.22.2.
Good For
- Developers looking for a 4B parameter model for general text generation.
- Applications requiring instruction-tuned responses.
- Experimentation with models fine-tuned using the TRL library.