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model_from_berturk_upos_22Jan
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: 0.0130
- Precision: 0.9961
- Recall: 0.9953
- F1: 0.9957
- Accuracy: 0.9967
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 | 0.2285 | 0.9100 | 0.9079 | 0.9089 | 0.9352 |
| No log | 2.0 | 340 | 0.1694 | 0.9303 | 0.9316 | 0.9310 | 0.9510 |
| 0.3728 | 3.0 | 510 | 0.1396 | 0.9420 | 0.9420 | 0.9420 | 0.9589 |
| 0.3728 | 4.0 | 680 | 0.1114 | 0.9561 | 0.9547 | 0.9554 | 0.9681 |
| 0.3728 | 5.0 | 850 | 0.0880 | 0.9657 | 0.9653 | 0.9655 | 0.9754 |
| 0.1318 | 6.0 | 1020 | 0.0670 | 0.9752 | 0.9730 | 0.9741 | 0.9814 |
| 0.1318 | 7.0 | 1190 | 0.0535 | 0.9801 | 0.9790 | 0.9795 | 0.9850 |
| 0.1318 | 8.0 | 1360 | 0.0407 | 0.9867 | 0.9842 | 0.9854 | 0.9894 |
| 0.0764 | 9.0 | 1530 | 0.0312 | 0.9902 | 0.9881 | 0.9892 | 0.9920 |
| 0.0764 | 10.0 | 1700 | 0.0254 | 0.9919 | 0.9903 | 0.9911 | 0.9935 |
| 0.0764 | 11.0 | 1870 | 0.0203 | 0.9939 | 0.9925 | 0.9932 | 0.9948 |
| 0.0466 | 12.0 | 2040 | 0.0169 | 0.9949 | 0.9939 | 0.9944 | 0.9958 |
| 0.0466 | 13.0 | 2210 | 0.0148 | 0.9955 | 0.9947 | 0.9951 | 0.9961 |
| 0.0466 | 14.0 | 2380 | 0.0135 | 0.9959 | 0.9949 | 0.9954 | 0.9966 |
| 0.0329 | 15.0 | 2550 | 0.0130 | 0.9961 | 0.9953 | 0.9957 | 0.9967 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
