---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification_AraEval24_basic_single
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# AraBERT_token_classification_AraEval24_basic_single

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: 0.8309
- Precision: 0.0558
- Recall: 0.0104
- F1: 0.0175
- Accuracy: 0.8720

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5987        | 1.0   | 2830  | 0.7729          | 1.0       | 0.0002 | 0.0004 | 0.8751   |
| 0.5694        | 2.0   | 5660  | 0.7337          | 0.0       | 0.0    | 0.0    | 0.8751   |
| 0.4944        | 3.0   | 8490  | 0.7180          | 0.0       | 0.0    | 0.0    | 0.8751   |
| 0.4569        | 4.0   | 11320 | 0.7157          | 0.0683    | 0.0039 | 0.0073 | 0.8746   |
| 0.4453        | 5.0   | 14150 | 0.7393          | 0.0973    | 0.0063 | 0.0119 | 0.8745   |
| 0.3859        | 6.0   | 16980 | 0.7607          | 0.0694    | 0.0042 | 0.0080 | 0.8745   |
| 0.3847        | 7.0   | 19810 | 0.7712          | 0.0838    | 0.0074 | 0.0136 | 0.8742   |
| 0.3582        | 8.0   | 22640 | 0.7805          | 0.0462    | 0.0081 | 0.0138 | 0.8723   |
| 0.3368        | 9.0   | 25470 | 0.8114          | 0.0542    | 0.0078 | 0.0136 | 0.8727   |
| 0.3185        | 10.0  | 28300 | 0.8309          | 0.0558    | 0.0104 | 0.0175 | 0.8720   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3