---
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: 0.1192
- Macro F1: 0.9610
- Accuracy: 0.9612
- Recall: 0.9612

## 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        | 0.9912 | 56   | 0.9585   | 0.1400          | 0.9582   | 0.9585 |
| No log        | 2.0    | 113  | 0.9601   | 0.1324          | 0.9600   | 0.9602 |
| No log        | 2.9912 | 169  | 0.9612   | 0.1192          | 0.9610   | 0.9612 |
| No log        | 4.0    | 226  | 0.9623   | 0.1393          | 0.9621   | 0.9623 |
| No log        | 4.9912 | 282  | 0.9596   | 0.1366          | 0.9596   | 0.9595 |
| No log        | 6.0    | 339  | 0.9607   | 0.1590          | 0.9606   | 0.9607 |
| No log        | 6.9912 | 395  | 0.9601   | 0.1741          | 0.9600   | 0.9602 |
| No log        | 8.0    | 452  | 0.9612   | 0.1824          | 0.9611   | 0.9612 |
| 0.0099        | 8.9912 | 504  | 0.1775   | 0.9617          | 0.9618   | 0.9617 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1