results
This model is a fine-tuned version of dbmdz/bert-base-turkish-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3292
- Accuracy: 0.9262
- Precision: 0.9262
- Recall: 0.9262
- F1: 0.9262
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: 16
- eval_batch_size: 16
- 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: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
0.2041 | 1.0 | 759 | 0.2459 | 0.9239 | 0.9272 | 0.9239 | 0.9254 |
0.1477 | 2.0 | 1518 | 0.2693 | 0.9255 | 0.9288 | 0.9255 | 0.9270 |
0.0877 | 3.0 | 2277 | 0.3292 | 0.9262 | 0.9262 | 0.9262 | 0.9262 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3
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Base model
dbmdz/bert-base-turkish-uncased