bert-base-multilingual-cased-ner-hrl
This model was finetuned on conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0799
- Precision: 0.9432
- Recall: 0.9549
- F1: 0.9490
- Accuracy: 0.9870
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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
|---|
| 0.0309 | 1.0 | 1756 | 0.0834 | 0.9307 | 0.9472 | 0.9389 | 0.9851 |
| 0.0157 | 2.0 | 3512 | 0.0784 | 0.9437 | 0.9536 | 0.9486 | 0.9873 |
| 0.0094 | 3.0 | 5268 | 0.0799 | 0.9432 | 0.9549 | 0.9490 | 0.9870 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.0.0+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
