qwen3-finetuned
This model is a fine-tuned version of Qwen/Qwen3-0.6B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1552
- Accuracy: 0.9651
- Precision: 0.9654
- Recall: 0.9651
- F1: 0.9651
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.3385 | 1.0 | 49 | 0.1535 | 0.9535 | 0.9543 | 0.9535 | 0.9534 |
| 0.5249 | 2.0 | 98 | 0.1429 | 0.9535 | 0.9535 | 0.9535 | 0.9535 |
| 0.0484 | 3.0 | 147 | 0.1552 | 0.9651 | 0.9654 | 0.9651 | 0.9651 |
Framework versions
- Transformers 5.10.2
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2