---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/roberta-base-finetuned-iso29148-f_nf_req-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-f_nf_req-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: 0.0019
- Validation Loss: 0.6444
- 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': 4710, '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 |
|:----------:|:---------------:|:-----:|
| 0.4775     | 0.3493          | 0     |
| 0.2723     | 0.3205          | 1     |
| 0.1702     | 0.3163          | 2     |
| 0.0925     | 0.3759          | 3     |
| 0.0803     | 0.4358          | 4     |
| 0.0444     | 0.5255          | 5     |
| 0.0227     | 0.5733          | 6     |
| 0.0342     | 0.5173          | 7     |
| 0.0231     | 0.5098          | 8     |
| 0.0144     | 0.5852          | 9     |
| 0.0067     | 0.6479          | 10    |
| 0.0039     | 0.7709          | 11    |
| 0.0222     | 0.5779          | 12    |
| 0.0144     | 0.6940          | 13    |
| 0.0213     | 0.5848          | 14    |
| 0.0047     | 0.6554          | 15    |
| 0.0036     | 0.6801          | 16    |
| 0.0011     | 0.7073          | 17    |
| 0.0082     | 0.7724          | 18    |
| 0.0084     | 0.6025          | 19    |
| 0.0009     | 0.6345          | 20    |
| 0.0034     | 0.6718          | 21    |
| 0.0032     | 0.6396          | 22    |
| 0.0030     | 0.6050          | 23    |
| 0.0005     | 0.6186          | 24    |
| 0.0006     | 0.6282          | 25    |
| 0.0005     | 0.6337          | 26    |
| 0.0004     | 0.6417          | 27    |
| 0.0003     | 0.6447          | 28    |
| 0.0019     | 0.6444          | 29    |


### Framework versions

- Transformers 4.40.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1