---
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