<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
akaashp15/distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0344
- Validation Loss: 0.0597
- Train Precision: 0.9253
- Train Recall: 0.9356
- Train F1: 0.9304
- Train Accuracy: 0.9836
- 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': 'Adam', '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}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.1990 | 0.0712 | 0.8974 | 0.9226 | 0.9098 | 0.9790 | 0 |
| 0.0544 | 0.0612 | 0.9148 | 0.9318 | 0.9232 | 0.9822 | 1 |
| 0.0344 | 0.0597 | 0.9253 | 0.9356 | 0.9304 | 0.9836 | 2 |
Framework versions
- Transformers 4.30.2
- TensorFlow 2.13.0-rc2
- Datasets 2.13.1
- Tokenizers 0.13.3
