metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: Sidziesama/Legal_NER_Support_Model_distilledbert
results: []
Sidziesama/Legal_NER_Support_Model_distilledbert
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0582
- Validation Loss: 0.0980
- Train Precision: 0.7952
- Train Recall: 0.8552
- Train F1: 0.8241
- Train Accuracy: 0.9716
- Epoch: 4
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': 3435, '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 |
|---|---|---|---|---|---|---|
| 0.4207 | 0.1608 | 0.6623 | 0.7498 | 0.7034 | 0.9557 | 0 |
| 0.1304 | 0.1118 | 0.7580 | 0.8116 | 0.7839 | 0.9668 | 1 |
| 0.0891 | 0.1012 | 0.7698 | 0.8525 | 0.8090 | 0.9701 | 2 |
| 0.0699 | 0.0976 | 0.7933 | 0.8507 | 0.8210 | 0.9713 | 3 |
| 0.0582 | 0.0980 | 0.7952 | 0.8552 | 0.8241 | 0.9716 | 4 |
Framework versions
- Transformers 4.39.3
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2