metadata
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: jborras18/conll_test
results: []
jborras18/conll_test
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: 0.0271
- Validation Loss: 0.0483
- Train Precision: 0.9252
- Train Recall: 0.9382
- Train F1: 0.9317
- Train Accuracy: 0.9868
- 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': 2631, '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 |
|---|---|---|---|---|---|---|
| 0.1611 | 0.0606 | 0.8987 | 0.9164 | 0.9074 | 0.9830 | 0 |
| 0.0427 | 0.0479 | 0.9227 | 0.9360 | 0.9293 | 0.9867 | 1 |
| 0.0271 | 0.0483 | 0.9252 | 0.9382 | 0.9317 | 0.9868 | 2 |
Framework versions
- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.9.0
- Tokenizers 0.13.2