metadata
license: mit
base_model: Jean-Baptiste/camembert-ner
tags:
- generated_from_keras_callback
model-index:
- name: Horus7/from_to_model
results: []
Horus7/from_to_model
This model is a fine-tuned version of Jean-Baptiste/camembert-ner on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.5479
- Validation Loss: 0.5319
- Train Precision: 0.5
- Train Recall: 0.5
- Train F1: 0.5
- Train Accuracy: 0.8333
- 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': 3, '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 |
|---|---|---|---|---|---|---|
| 0.7905 | 0.8124 | 0.5 | 0.5 | 0.5 | 0.8333 | 0 |
| 0.6434 | 0.6277 | 0.5 | 0.5 | 0.5 | 0.8333 | 1 |
| 0.5479 | 0.5319 | 0.5 | 0.5 | 0.5 | 0.8333 | 2 |
Framework versions
- Transformers 4.35.0
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1