| --- |
| license: apache-2.0 |
| base_model: bert-base-cased |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: chosenone80/bert-ner-test-1 |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # chosenone80/bert-ner-test-1 |
|
|
| This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 0.1319 |
| - Validation Loss: 0.0479 |
| - Train Precision: 0.9163 |
| - Train Recall: 0.9298 |
| - Train F1: 0.9230 |
| - Train Accuracy: 0.9874 |
| - Epoch: 0 |
|
|
| ## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 877, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
| - training_precision: float32 |
|
|
| ### Training results |
|
|
| | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch | |
| |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:| |
| | 0.1319 | 0.0479 | 0.9163 | 0.9298 | 0.9230 | 0.9874 | 0 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - TensorFlow 2.15.0 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
|
|
