---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine_tuned_mix400k_arabert
  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. -->

# fine_tuned_mix400k_arabert

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1851
- Accuracy: 0.9674
- Precision: 0.9835
- Recall: 0.9723
- F1: 0.9778

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.113         | 1.0   | 42279  | 0.1089          | 0.9541   | 0.9962    | 0.9414 | 0.9680 |
| 0.0957        | 2.0   | 84558  | 0.1094          | 0.9639   | 0.9869    | 0.9638 | 0.9752 |
| 0.0833        | 3.0   | 126837 | 0.1061          | 0.9641   | 0.9900    | 0.9611 | 0.9753 |
| 0.0691        | 4.0   | 169116 | 0.1558          | 0.9677   | 0.9845    | 0.9716 | 0.9780 |
| 0.0552        | 5.0   | 211395 | 0.1193          | 0.9676   | 0.9843    | 0.9717 | 0.9780 |
| 0.0411        | 6.0   | 253674 | 0.1851          | 0.9674   | 0.9835    | 0.9723 | 0.9778 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1