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---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/roberta-base-finetuned-iso29148-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/roberta-base-finetuned-iso29148-promise-km-labels-nf-subclasses-cls
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0124
- Validation Loss: 0.1623
- Epoch: 29
## 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': 1770, '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 |
|:----------:|:---------------:|:-----:|
| 2.1848 | 1.7407 | 0 |
| 1.2611 | 0.8464 | 1 |
| 0.5377 | 0.4928 | 2 |
| 0.2843 | 0.2790 | 3 |
| 0.1531 | 0.3657 | 4 |
| 0.1186 | 0.1997 | 5 |
| 0.0646 | 0.1742 | 6 |
| 0.0498 | 0.1731 | 7 |
| 0.0417 | 0.1709 | 8 |
| 0.0351 | 0.1689 | 9 |
| 0.0309 | 0.1659 | 10 |
| 0.0270 | 0.1674 | 11 |
| 0.0255 | 0.1687 | 12 |
| 0.0229 | 0.1665 | 13 |
| 0.0210 | 0.1673 | 14 |
| 0.0193 | 0.1677 | 15 |
| 0.0185 | 0.1664 | 16 |
| 0.0168 | 0.1658 | 17 |
| 0.0162 | 0.1649 | 18 |
| 0.0156 | 0.1670 | 19 |
| 0.0150 | 0.1678 | 20 |
| 0.0144 | 0.1656 | 21 |
| 0.0141 | 0.1653 | 22 |
| 0.0138 | 0.1662 | 23 |
| 0.0132 | 0.1668 | 24 |
| 0.0127 | 0.1629 | 25 |
| 0.0125 | 0.1614 | 26 |
| 0.0123 | 0.1619 | 27 |
| 0.0122 | 0.1624 | 28 |
| 0.0124 | 0.1623 | 29 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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