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notmaineyy/bert-base-multilingual-cased-finetuned-ner
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0248
- Validation Loss: 0.0568
- Train Precision: 0.9424
- Train Recall: 0.9471
- Train F1: 0.9448
- Train Accuracy: 0.9863
- Epoch: 2
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10530, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.1335 | 0.0705 | 0.9152 | 0.9204 | 0.9178 | 0.9806 | 0 |
| 0.0497 | 0.0562 | 0.9335 | 0.9472 | 0.9403 | 0.9851 | 1 |
| 0.0248 | 0.0568 | 0.9424 | 0.9471 | 0.9448 | 0.9863 | 2 |
Framework versions
- Transformers 4.21.0
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
