The krishnaTO/qwen3-finetuned model is a fine-tuned version of the Qwen/Qwen3-0.6B architecture, featuring 0.8 billion parameters and a context length of 32768 tokens. Developed by krishnaTO, this model has undergone a single epoch of fine-tuning, achieving a validation loss of 3.7385. Its specific applications and primary differentiators are not detailed in the available documentation, suggesting it may be a foundational or experimental fine-tune.
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Model Overview
The krishnaTO/qwen3-finetuned model is a fine-tuned variant of the Qwen/Qwen3-0.6B base model, developed by krishnaTO. It has 0.8 billion parameters and supports a context length of 32768 tokens. The fine-tuning process involved a single epoch, resulting in a validation loss of 3.7385.
Training Details
The model was trained using the following key hyperparameters:
- Learning Rate: 2e-08
- Batch Sizes:
train_batch_sizeof 4,eval_batch_sizeof 8, withgradient_accumulation_stepsof 4, leading to atotal_train_batch_sizeof 16. - Optimizer: ADAMW_TORCH_FUSED with default betas and epsilon.
- LR Scheduler: Linear type.
- Epochs: 1
Limitations
The available documentation does not specify the dataset used for fine-tuning, nor does it detail the intended uses or known limitations of this particular fine-tuned version. Users should exercise caution and conduct further evaluation to determine its suitability for specific tasks.