Turna
This model is a fine-tuned version of boun-tabi-LMG/TURNA on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9589
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0 | 1.0 | 230 | nan | 0.0 | 0.0 | 0.0 | 0.9615 |
0.0 | 2.0 | 460 | nan | 0.0 | 0.0 | 0.0 | 0.9615 |
0.0 | 3.0 | 690 | nan | 0.0 | 0.0 | 0.0 | 0.9615 |
0.0 | 4.0 | 920 | nan | 0.0 | 0.0 | 0.0 | 0.9615 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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