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---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/bert-base-uncased-finetuned-iso29148-sward-on-promise-km-labels-nf-subclasses-cls
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. -->
# kasrahabib/bert-base-uncased-finetuned-iso29148-sward-on-promise-km-labels-nf-subclasses-cls
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0007
- Validation Loss: 1.0381
- Epoch: 14
## 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': 123615, '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 | Epoch |
|:----------:|:---------------:|:-----:|
| 0.7510 | 0.5526 | 0 |
| 0.3329 | 0.5541 | 1 |
| 0.1715 | 0.6226 | 2 |
| 0.1029 | 0.6412 | 3 |
| 0.0699 | 0.7550 | 4 |
| 0.0500 | 0.7140 | 5 |
| 0.0372 | 0.7635 | 6 |
| 0.0250 | 0.8047 | 7 |
| 0.0205 | 0.8339 | 8 |
| 0.0126 | 0.8673 | 9 |
| 0.0096 | 0.9238 | 10 |
| 0.0068 | 0.9350 | 11 |
| 0.0029 | 1.0098 | 12 |
| 0.0016 | 1.0402 | 13 |
| 0.0007 | 1.0381 | 14 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
|