---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: kasrahabib/roberta-base-finetuned-iso29148-promise-km-labels-all-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-all-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: 0.0093
- Validation Loss: 0.1119
- 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': 2370, '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 |
|:----------:|:---------------:|:-----:|
| 2.2048     | 1.6598          | 0     |
| 1.1216     | 0.5631          | 1     |
| 0.3896     | 0.2574          | 2     |
| 0.1978     | 0.1997          | 3     |
| 0.1204     | 0.1526          | 4     |
| 0.0676     | 0.1887          | 5     |
| 0.0435     | 0.1289          | 6     |
| 0.0338     | 0.1219          | 7     |
| 0.0291     | 0.1140          | 8     |
| 0.0372     | 0.1829          | 9     |
| 0.0655     | 0.2036          | 10    |
| 0.0654     | 0.3368          | 11    |
| 0.1950     | 0.3786          | 12    |
| 0.0544     | 0.1708          | 13    |
| 0.0195     | 0.1446          | 14    |
| 0.0166     | 0.1364          | 15    |
| 0.0154     | 0.1302          | 16    |
| 0.0136     | 0.1272          | 17    |
| 0.0127     | 0.1251          | 18    |
| 0.0119     | 0.1248          | 19    |
| 0.0115     | 0.1231          | 20    |
| 0.0112     | 0.1214          | 21    |
| 0.0107     | 0.1190          | 22    |
| 0.0104     | 0.1166          | 23    |
| 0.0100     | 0.1157          | 24    |
| 0.0095     | 0.1131          | 25    |
| 0.0096     | 0.1126          | 26    |
| 0.0092     | 0.1120          | 27    |
| 0.0094     | 0.1119          | 28    |
| 0.0093     | 0.1119          | 29    |


### Framework versions

- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1