distilbert-base-multilingual-cased-mapa_coarse-ner
This model is a fine-tuned version of distilbert-base-multilingual-cased on the lextreme dataset. It achieves the following results on the evaluation set:
- Loss: 0.0882
- Precision: 0.7191
- Recall: 0.6453
- F1: 0.6802
- Accuracy: 0.9879
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0248 | 1.0 | 1739 | 0.0528 | 0.7451 | 0.5805 | 0.6525 | 0.9871 |
| 0.0181 | 2.0 | 3478 | 0.0595 | 0.7369 | 0.5749 | 0.6459 | 0.9875 |
| 0.0121 | 3.0 | 5217 | 0.0499 | 0.7404 | 0.6280 | 0.6796 | 0.9879 |
| 0.0088 | 4.0 | 6956 | 0.0634 | 0.6912 | 0.6334 | 0.6610 | 0.9875 |
| 0.0072 | 5.0 | 8695 | 0.0625 | 0.7109 | 0.6478 | 0.6779 | 0.9880 |
| 0.0052 | 6.0 | 10434 | 0.0702 | 0.7098 | 0.6518 | 0.6796 | 0.9878 |
| 0.0041 | 7.0 | 12173 | 0.0733 | 0.7176 | 0.6429 | 0.6782 | 0.9878 |
| 0.0026 | 8.0 | 13912 | 0.0779 | 0.7198 | 0.6540 | 0.6853 | 0.9879 |
| 0.0019 | 9.0 | 15651 | 0.0875 | 0.7181 | 0.6419 | 0.6779 | 0.9877 |
| 0.0018 | 10.0 | 17390 | 0.0882 | 0.7191 | 0.6453 | 0.6802 | 0.9879 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2