fine_tuned_roct
This model is a fine-tuned version of Qwen/Qwen2-1.5B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4360
- Accuracy: 0.8990
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 |
---|---|---|---|---|
0.9049 | 0.0309 | 100 | 0.3296 | 0.8785 |
0.4092 | 0.0617 | 200 | 0.3509 | 0.8788 |
0.3024 | 0.0926 | 300 | 0.5640 | 0.8795 |
0.6762 | 0.1235 | 400 | 0.4360 | 0.8990 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
Qwen/Qwen2-1.5B