| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: apriadiazriel/bert_base_ncbi |
| results: [] |
| datasets: |
| - ncbi/ncbi_disease |
| language: |
| - en |
| metrics: |
| - f1 |
| pipeline_tag: token-classification |
| --- |
| |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should |
| probably proofread and complete it, then remove this comment. --> |
|
|
| # apriadiazriel/bert_base_ncbi |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [NCBI disease](https://huggingface.co/datasets/ncbi/ncbi_disease) dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.0168 |
| - Validation Loss: 0.0518 |
| - Precision: 0.8 |
| - Recall: 0.8640 |
| - F1: 0.8308 |
| - Accuracy: 0.9860 |
| - Epoch: 9 |
|
|
| ## 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': 1017, '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 | Precision | Recall | F1 | Accuracy | Epoch | |
| |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
| | 0.1130 | 0.0547 | 0.7364 | 0.7916 | 0.7630 | 0.9832 | 0 | |
| | 0.0335 | 0.0497 | 0.7836 | 0.8513 | 0.8161 | 0.9850 | 1 | |
| | 0.0213 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 2 | |
| | 0.0166 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 3 | |
| | 0.0173 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 4 | |
| | 0.0174 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 5 | |
| | 0.0168 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 6 | |
| | 0.0172 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 7 | |
| | 0.0167 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 8 | |
| | 0.0168 | 0.0518 | 0.8 | 0.8640 | 0.8308 | 0.9860 | 9 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.3 |
| - TensorFlow 2.18.0 |
| - Datasets 3.3.1 |
| - Tokenizers 0.21.0 |
