ajinkyaT/albert-japanese-v2-finetuned-ner
This model is a fine-tuned version of ajinkyaT/albert-japanese-v2-finetuned-ner on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1292
- Validation Loss: 0.1499
- Train Precision: 0.6817
- Train Recall: 0.6951
- Train F1: 0.6883
- Train Accuracy: 0.9594
- Epoch: 9
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': 1320, '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 |
|---|---|---|---|---|---|---|
| 0.1299 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 4 |
| 0.1306 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 5 |
| 0.1296 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 6 |
| 0.1292 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 7 |
| 0.1306 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 8 |
| 0.1292 | 0.1499 | 0.6817 | 0.6951 | 0.6883 | 0.9594 | 9 |
Framework versions
- Transformers 4.23.1
- TensorFlow 2.8.2
- Datasets 2.5.2
- Tokenizers 0.13.1