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---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/roberta-base-finetuned-iso29148-sward-on-promise-km-labels-f-nf-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-sward-on-promise-km-labels-f-nf-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: 0.0025
- Validation Loss: 0.4430
- 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': 123645, '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 |
|:----------:|:---------------:|:-----:|
| 0.3370 | 0.2402 | 0 |
| 0.1937 | 0.2777 | 1 |
| 0.1167 | 0.2346 | 2 |
| 0.0819 | 0.2329 | 3 |
| 0.0624 | 0.2889 | 4 |
| 0.0458 | 0.2796 | 5 |
| 0.0330 | 0.3695 | 6 |
| 0.0234 | 0.3125 | 7 |
| 0.0174 | 0.4382 | 8 |
| 0.0142 | 0.3535 | 9 |
| 0.0098 | 0.4172 | 10 |
| 0.0085 | 0.3862 | 11 |
| 0.0053 | 0.3860 | 12 |
| 0.0040 | 0.4372 | 13 |
| 0.0025 | 0.4430 | 14 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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