---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_AraEval24_18_labels_mlm1k_augmented
  results: []
---

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# AraBERT_token_classification_AraEval24_18_labels_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: 0.9374
- Precision: 0.0475
- Recall: 0.0165
- F1: 0.0245
- Accuracy: 0.8620

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5534        | 1.0   | 7396  | 0.7643          | 0.0031    | 0.0002 | 0.0003 | 0.8712   |
| 0.4414        | 2.0   | 14792 | 0.7713          | 0.0159    | 0.0018 | 0.0032 | 0.8638   |
| 0.3961        | 3.0   | 22188 | 0.7715          | 0.0137    | 0.0014 | 0.0026 | 0.8684   |
| 0.3484        | 4.0   | 29584 | 0.7929          | 0.0421    | 0.0065 | 0.0113 | 0.8661   |
| 0.3131        | 5.0   | 36980 | 0.8180          | 0.04      | 0.0107 | 0.0169 | 0.8578   |
| 0.2899        | 6.0   | 44376 | 0.8650          | 0.0448    | 0.0098 | 0.0161 | 0.8625   |
| 0.2682        | 7.0   | 51772 | 0.8725          | 0.0556    | 0.0186 | 0.0279 | 0.8551   |
| 0.2433        | 8.0   | 59168 | 0.8841          | 0.0521    | 0.0146 | 0.0228 | 0.8603   |
| 0.2384        | 9.0   | 66564 | 0.9149          | 0.0502    | 0.0155 | 0.0237 | 0.8635   |
| 0.2094        | 10.0  | 73960 | 0.9374          | 0.0475    | 0.0165 | 0.0245 | 0.8620   |


### Framework versions

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