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bert-fine-grained
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: 1.1308
- Accuracy: 0.5761
- F1: 0.5655
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0917 | 1.0 | 2188 | 1.0668 | 0.5789 | 0.5448 |
| 0.9603 | 2.0 | 4376 | 1.0620 | 0.5868 | 0.5718 |
| 0.8047 | 3.0 | 6564 | 1.1308 | 0.5761 | 0.5655 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1
