---
license: mit
base_model: Davlan/xlm-roberta-base-finetuned-arabic
tags:
- generated_from_keras_callback
model-index:
- name: betteib/xlm-tn-20epochs
  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. -->

# betteib/xlm-tn-20epochs

This model is a fine-tuned version of [Davlan/xlm-roberta-base-finetuned-arabic](https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 6.7068
- Train Accuracy: 0.0290
- Validation Loss: 6.6661
- Validation Accuracy: 0.0290
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 18848, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 992, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 9.7281     | 0.0031         | 9.4281          | 0.0045              | 0     |
| 9.2184     | 0.0051         | 8.9814          | 0.0060              | 1     |
| 8.7336     | 0.0068         | 8.4005          | 0.0084              | 2     |
| 8.1287     | 0.0109         | 7.7969          | 0.0133              | 3     |
| 7.6665     | 0.0159         | 7.4295          | 0.0222              | 4     |
| 7.3938     | 0.0233         | 7.1783          | 0.0289              | 5     |
| 7.2079     | 0.0287         | 7.0257          | 0.0286              | 6     |
| 7.0785     | 0.0292         | 6.9028          | 0.0291              | 7     |
| 6.9777     | 0.0294         | 6.8739          | 0.0287              | 8     |
| 6.9034     | 0.0292         | 6.8083          | 0.0281              | 9     |
| 6.8549     | 0.0292         | 6.8099          | 0.0280              | 10    |
| 6.7978     | 0.0292         | 6.7450          | 0.0286              | 11    |
| 6.7555     | 0.0291         | 6.7420          | 0.0281              | 12    |
| 6.7267     | 0.0293         | 6.6804          | 0.0291              | 13    |
| 6.7068     | 0.0290         | 6.6661          | 0.0290              | 14    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.19.1
- Tokenizers 0.13.3