metadata
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_keras_callback
model-index:
- name: Kikia26/FineTunePubMedBertWithTensorflowKeras2
results: []
Kikia26/FineTunePubMedBertWithTensorflowKeras2
This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.2240
- Validation Loss: 0.3445
- Train Precision: 0.6355
- Train Recall: 0.6730
- Train F1: 0.6537
- Train Accuracy: 0.9041
- Epoch: 7
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': 5e-05, 'decay_steps': 200, '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 |
|---|---|---|---|---|---|---|
| 1.5823 | 0.9047 | 0.0 | 0.0 | 0.0 | 0.7808 | 0 |
| 0.9053 | 0.6998 | 0.5303 | 0.0738 | 0.1296 | 0.8106 | 1 |
| 0.6980 | 0.5341 | 0.7038 | 0.3861 | 0.4986 | 0.8591 | 2 |
| 0.5206 | 0.4613 | 0.6213 | 0.5295 | 0.5718 | 0.8753 | 3 |
| 0.4110 | 0.4201 | 0.6292 | 0.5549 | 0.5897 | 0.8836 | 4 |
| 0.3260 | 0.3918 | 0.6306 | 0.5907 | 0.6100 | 0.8937 | 5 |
| 0.2682 | 0.3682 | 0.5989 | 0.6709 | 0.6328 | 0.8985 | 6 |
| 0.2240 | 0.3445 | 0.6355 | 0.6730 | 0.6537 | 0.9041 | 7 |
Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0