---
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