---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_AraEval24_back_translation_mlm1k_augmented
  results: []
---

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# AraBERT_token_classification_AraEval24_back_translation_mlm1k_augmented

This model is a fine-tuned version of [aubmindlab/bert-base-arabert](https://huggingface.co/aubmindlab/bert-base-arabert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9905
- Precision: 0.0511
- Recall: 0.0181
- F1: 0.0267
- Accuracy: 0.8621

## 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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4984        | 1.0   | 7951  | 0.7412          | 0.0194    | 0.0011 | 0.0020 | 0.8715   |
| 0.4115        | 2.0   | 15902 | 0.7585          | 0.0571    | 0.0035 | 0.0066 | 0.8721   |
| 0.3718        | 3.0   | 23853 | 0.7859          | 0.0720    | 0.0049 | 0.0092 | 0.8724   |
| 0.3331        | 4.0   | 31804 | 0.8117          | 0.0431    | 0.0062 | 0.0108 | 0.8679   |
| 0.3017        | 5.0   | 39755 | 0.8332          | 0.0477    | 0.0097 | 0.0161 | 0.8658   |
| 0.2682        | 6.0   | 47706 | 0.8462          | 0.0540    | 0.0123 | 0.0200 | 0.8628   |
| 0.2627        | 7.0   | 55657 | 0.8597          | 0.0553    | 0.0125 | 0.0204 | 0.8636   |
| 0.2372        | 8.0   | 63608 | 0.9231          | 0.0556    | 0.0149 | 0.0236 | 0.8646   |
| 0.2208        | 9.0   | 71559 | 0.9553          | 0.0567    | 0.0160 | 0.0250 | 0.8657   |
| 0.2206        | 10.0  | 79510 | 0.9905          | 0.0511    | 0.0181 | 0.0267 | 0.8621   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.2
- Tokenizers 0.13.3