---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_AraEval24_18_labels_augmented_fixed2
  results: []
---

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# AraBERT_token_classification_AraEval24_18_labels_augmented_fixed2

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: 0.8169
- Precision: 0.0952
- Recall: 0.0280
- F1: 0.0432
- Accuracy: 0.8714

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.684         | 1.0   | 3215  | 0.7004          | 0.0       | 0.0    | 0.0    | 0.8767   |
| 0.5935        | 2.0   | 6430  | 0.6946          | 0.0909    | 0.0005 | 0.0010 | 0.8765   |
| 0.5262        | 3.0   | 9645  | 0.7115          | 0.0952    | 0.0097 | 0.0176 | 0.8755   |
| 0.4585        | 4.0   | 12860 | 0.7140          | 0.0788    | 0.0204 | 0.0324 | 0.8718   |
| 0.4415        | 5.0   | 16075 | 0.7314          | 0.0982    | 0.0104 | 0.0188 | 0.8750   |
| 0.39          | 6.0   | 19290 | 0.7542          | 0.0942    | 0.0167 | 0.0284 | 0.8734   |
| 0.3668        | 7.0   | 22505 | 0.7570          | 0.0947    | 0.0230 | 0.0371 | 0.8721   |
| 0.3314        | 8.0   | 25720 | 0.8040          | 0.0887    | 0.0290 | 0.0437 | 0.8712   |
| 0.308         | 9.0   | 28935 | 0.7975          | 0.0977    | 0.0295 | 0.0454 | 0.8714   |
| 0.3007        | 10.0  | 32150 | 0.8169          | 0.0952    | 0.0280 | 0.0432 | 0.8714   |


### Framework versions

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