---
base_model: aubmindlab/bert-base-arabertv2
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
model-index:
- name: AraBert-finetuned-text-classification
  results: []
---

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

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv2](https://huggingface.co/aubmindlab/bert-base-arabertv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1147
- Macro F1: 0.9623
- Accuracy: 0.9623
- Recall: 0.9622

## 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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Accuracy | Validation Loss | Macro F1 | Recall |
|:-------------:|:-----:|:----:|:--------:|:---------------:|:--------:|:------:|
| No log        | 0.99  | 56   | 0.9430   | 0.1530          | 0.9427   | 0.9425 |
| No log        | 1.99  | 112  | 0.9579   | 0.1230          | 0.9577   | 0.9577 |
| No log        | 3.0   | 169  | 0.9607   | 0.1287          | 0.9605   | 0.9608 |
| No log        | 3.99  | 225  | 0.9618   | 0.1296          | 0.9616   | 0.9618 |
| No log        | 5.0   | 282  | 0.9623   | 0.1147          | 0.9623   | 0.9622 |
| No log        | 5.99  | 338  | 0.9612   | 0.1500          | 0.9611   | 0.9612 |
| No log        | 7.0   | 395  | 0.9601   | 0.1953          | 0.9599   | 0.9602 |
| No log        | 7.99  | 451  | 0.9640   | 0.1713          | 0.9639   | 0.9640 |
| 0.0526        | 9.0   | 508  | 0.9646   | 0.1748          | 0.9644   | 0.9645 |
| 0.0526        | 9.92  | 560  | 0.9646   | 0.1768          | 0.9644   | 0.9645 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2