metadata
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Ermira/bert-base-multilingual-uncased-finetuned-ner
results: []
Ermira/bert-base-multilingual-uncased-finetuned-ner
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0284
- Validation Loss: 0.0543
- Train Precision: 0.9354
- Train Recall: 0.9459
- Train F1: 0.9406
- Train Accuracy: 0.9860
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|---|---|---|---|---|---|---|
| 0.1485 | 0.0642 | 0.9083 | 0.9288 | 0.9184 | 0.9820 | 0 |
| 0.0482 | 0.0561 | 0.9270 | 0.9424 | 0.9347 | 0.9846 | 1 |
| 0.0284 | 0.0543 | 0.9354 | 0.9459 | 0.9406 | 0.9860 | 2 |
Framework versions
- Transformers 4.41.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1