Alu017/qwen3-finetuned
Alu017/qwen3-finetuned is a 0.8 billion parameter causal language model, fine-tuned from Qwen/Qwen3-0.6B. This model is a smaller variant within the Qwen3 family, featuring a 32768-token context length. It is designed for general language tasks, with its specific fine-tuning dataset and primary differentiators currently unspecified beyond its base architecture and parameter count.
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Model Overview
Alu017/qwen3-finetuned is a 0.8 billion parameter language model, derived from the Qwen/Qwen3-0.6B base model. It was fine-tuned over 2 epochs using a linear learning rate scheduler and AdamW_Torch_Fused optimizer, achieving a validation loss of 2.8675. The training utilized mixed-precision (Native AMP) with a total batch size of 16.
Key Training Details
- Base Model: Qwen/Qwen3-0.6B
- Parameters: 0.8 billion
- Context Length: 32768 tokens
- Learning Rate: 2e-05
- Optimizer: AdamW_Torch_Fused
- Epochs: 2
- Final Validation Loss: 2.8675
Current Limitations
Specific details regarding the fine-tuning dataset, intended uses, and unique capabilities or differentiators of this particular fine-tuned version are not provided in the available documentation. Users should be aware that its primary strengths and ideal applications are currently undefined beyond its foundational Qwen3 architecture.