berturk-128k-keyword-discriminator
This model is a fine-tuned version of dbmdz/bert-base-turkish-128k-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3828
- Precision: 0.6791
- Recall: 0.7234
- Accuracy: 0.9294
- F1: 0.7006
- Ent/precision: 0.6931
- Ent/accuracy: 0.7715
- Ent/f1: 0.7302
- Con/precision: 0.6473
- Con/accuracy: 0.6282
- Con/f1: 0.6376
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | Ent/precision | Ent/accuracy | Ent/f1 | Con/precision | Con/accuracy | Con/f1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.1632 | 1.0 | 1875 | 0.1637 | 0.6661 | 0.6900 | 0.9320 | 0.6778 | 0.6649 | 0.7401 | 0.7005 | 0.6692 | 0.5907 | 0.6275 |
| 0.1151 | 2.0 | 3750 | 0.1709 | 0.6538 | 0.7446 | 0.9292 | 0.6963 | 0.6682 | 0.7864 | 0.7225 | 0.6223 | 0.6619 | 0.6415 |
| 0.0817 | 3.0 | 5625 | 0.1931 | 0.6667 | 0.7292 | 0.9294 | 0.6965 | 0.6843 | 0.7677 | 0.7236 | 0.6290 | 0.6529 | 0.6407 |
| 0.057 | 4.0 | 7500 | 0.2375 | 0.6578 | 0.7486 | 0.9277 | 0.7002 | 0.6708 | 0.7950 | 0.7277 | 0.6284 | 0.6567 | 0.6422 |
| 0.041 | 5.0 | 9375 | 0.2765 | 0.6683 | 0.7390 | 0.9284 | 0.7019 | 0.6834 | 0.7821 | 0.7294 | 0.6351 | 0.6538 | 0.6444 |
| 0.0297 | 6.0 | 11250 | 0.3128 | 0.6811 | 0.7249 | 0.9295 | 0.7023 | 0.6979 | 0.7710 | 0.7327 | 0.6438 | 0.6334 | 0.6386 |
| 0.0211 | 7.0 | 13125 | 0.3633 | 0.6780 | 0.7236 | 0.9290 | 0.7001 | 0.6919 | 0.7722 | 0.7299 | 0.6463 | 0.6273 | 0.6366 |
| 0.0165 | 8.0 | 15000 | 0.3828 | 0.6791 | 0.7234 | 0.9294 | 0.7006 | 0.6931 | 0.7715 | 0.7302 | 0.6473 | 0.6282 | 0.6376 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1