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model_from_berturk_upos_22Jan_val_on_dev_v1
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4600
- Precision: 0.8894
- Recall: 0.8931
- F1: 0.8913
- Accuracy: 0.9217
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: 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 170 | 0.3259 | 0.8864 | 0.8851 | 0.8857 | 0.9170 |
| No log | 2.0 | 340 | 0.2976 | 0.8991 | 0.9005 | 0.8998 | 0.9271 |
| 0.3859 | 3.0 | 510 | 0.2988 | 0.8970 | 0.8981 | 0.8976 | 0.9257 |
| 0.3859 | 4.0 | 680 | 0.3131 | 0.8977 | 0.8984 | 0.8981 | 0.9267 |
| 0.3859 | 5.0 | 850 | 0.3291 | 0.8943 | 0.8974 | 0.8958 | 0.9246 |
| 0.1338 | 6.0 | 1020 | 0.3298 | 0.8974 | 0.8984 | 0.8979 | 0.9253 |
| 0.1338 | 7.0 | 1190 | 0.3538 | 0.8908 | 0.8950 | 0.8929 | 0.9222 |
| 0.1338 | 8.0 | 1360 | 0.3879 | 0.8903 | 0.8921 | 0.8912 | 0.9220 |
| 0.0798 | 9.0 | 1530 | 0.3852 | 0.8929 | 0.8933 | 0.8931 | 0.9228 |
| 0.0798 | 10.0 | 1700 | 0.4111 | 0.8873 | 0.8896 | 0.8884 | 0.9196 |
| 0.0798 | 11.0 | 1870 | 0.4254 | 0.8928 | 0.8940 | 0.8934 | 0.9231 |
| 0.0507 | 12.0 | 2040 | 0.4476 | 0.8911 | 0.8930 | 0.8921 | 0.9224 |
| 0.0507 | 13.0 | 2210 | 0.4478 | 0.8900 | 0.8926 | 0.8913 | 0.9220 |
| 0.0507 | 14.0 | 2380 | 0.4563 | 0.8896 | 0.8931 | 0.8914 | 0.9217 |
| 0.0357 | 15.0 | 2550 | 0.4600 | 0.8894 | 0.8931 | 0.8913 | 0.9217 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
