metadata
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_keras_callback
model-index:
- name: Kikia26/FineTunePubMedBertWithTensorflowKeras
results: []
Kikia26/FineTunePubMedBertWithTensorflowKeras
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: 0.3591
- Validation Loss: 0.4051
- Train Precision: 0.5896
- Train Recall: 0.6245
- Train F1: 0.6066
- Train Accuracy: 0.8857
- Epoch: 5
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': 100, '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 |
|---|---|---|---|---|---|---|
| 1.2909 | 0.7719 | 0.0 | 0.0 | 0.0 | 0.7813 | 0 |
| 0.8005 | 0.5567 | 0.4313 | 0.3776 | 0.4027 | 0.8372 | 1 |
| 0.5460 | 0.4551 | 0.5509 | 0.5823 | 0.5662 | 0.8676 | 2 |
| 0.4141 | 0.4381 | 0.5443 | 0.6477 | 0.5915 | 0.8732 | 3 |
| 0.3626 | 0.4051 | 0.5896 | 0.6245 | 0.6066 | 0.8857 | 4 |
| 0.3591 | 0.4051 | 0.5896 | 0.6245 | 0.6066 | 0.8857 | 5 |
Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0