boradorish/qwen3-4b-base-prompt
The boradorish/qwen3-4b-base-prompt is a 4 billion parameter language model, fine-tuned from Qwen/Qwen3-4B by boradorish. This model has been specifically fine-tuned on the 'sunny_reasoning' dataset, indicating an optimization for reasoning tasks. It features a 32768 token context length and demonstrates a low training loss of 0.0087 on its evaluation set, suggesting strong performance in its specialized domain.
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Model Overview
The boradorish/qwen3-4b-base-prompt is a 4 billion parameter language model, derived from the Qwen/Qwen3-4B architecture. It has been fine-tuned by boradorish using the 'sunny_reasoning' dataset, suggesting a specialization in tasks requiring logical inference or problem-solving capabilities. The model maintains a substantial context window of 32768 tokens, allowing it to process and generate longer sequences of text.
Key Training Details
- Base Model: Qwen/Qwen3-4B
- Fine-tuning Dataset:
sunny_reasoning - Evaluation Loss: Achieved a low validation loss of 0.0087, indicating effective learning during the fine-tuning process.
- Hyperparameters: Training involved a learning rate of 2e-05, a total batch size of 32 (with gradient accumulation), and 3 epochs using an AdamW optimizer and cosine learning rate scheduler.
Potential Use Cases
Given its fine-tuning on a reasoning-focused dataset, this model is likely well-suited for applications that require:
- Logical Deduction: Tasks involving drawing conclusions from given premises.
- Problem Solving: Scenarios where the model needs to analyze information and propose solutions.
- Structured Question Answering: Answering questions that require more than simple fact retrieval, potentially involving multi-step reasoning.
Further information regarding specific intended uses and limitations would require additional details from the model developer.