---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine_tuned_mix200k_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_mix200k_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: 0.2296
- Accuracy: 0.9391
- Precision: 0.9725
- Recall: 0.9427
- F1: 0.9574

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1891        | 1.0   | 19794 | 0.1615          | 0.9230   | 0.9889    | 0.9041 | 0.9446 |
| 0.1533        | 2.0   | 39588 | 0.1852          | 0.9340   | 0.9804    | 0.9276 | 0.9533 |
| 0.1287        | 3.0   | 59382 | 0.2530          | 0.9387   | 0.9658    | 0.9491 | 0.9574 |
| 0.1032        | 4.0   | 79176 | 0.2296          | 0.9391   | 0.9725    | 0.9427 | 0.9574 |


### Framework versions

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