---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: AraBERT_token_classification__AraEval24_merged_rassd
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# AraBERT_token_classification__AraEval24_merged_rassd

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: 0.8706
- Precision: 0.0867
- Recall: 0.0203
- F1: 0.0329
- Accuracy: 0.8593

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6887        | 1.0   | 2878  | 0.7951          | 0.0       | 0.0    | 0.0    | 0.8632   |
| 0.6215        | 2.0   | 5756  | 0.7865          | 0.0667    | 0.0010 | 0.0020 | 0.8635   |
| 0.5597        | 3.0   | 8634  | 0.7852          | 0.0901    | 0.0025 | 0.0048 | 0.8634   |
| 0.5221        | 4.0   | 11512 | 0.7851          | 0.1001    | 0.0115 | 0.0206 | 0.8622   |
| 0.4521        | 5.0   | 14390 | 0.7992          | 0.0772    | 0.0063 | 0.0117 | 0.8627   |
| 0.4411        | 6.0   | 17268 | 0.8035          | 0.0873    | 0.0084 | 0.0154 | 0.8625   |
| 0.4185        | 7.0   | 20146 | 0.8330          | 0.0714    | 0.0092 | 0.0162 | 0.8619   |
| 0.3954        | 8.0   | 23024 | 0.8511          | 0.0943    | 0.0158 | 0.0271 | 0.8619   |
| 0.3688        | 9.0   | 25902 | 0.8527          | 0.0936    | 0.0158 | 0.0271 | 0.8608   |
| 0.3575        | 10.0  | 28780 | 0.8706          | 0.0867    | 0.0203 | 0.0329 | 0.8593   |


### Framework versions

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