---
base_model: asafaya/bert-base-arabic
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Improved-Arabic-bert-nodropout
  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. -->

# Improved-Arabic-bert-nodropout

This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8352
- Accuracy: 0.83

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5185        | 0.55  | 50   | 0.3813          | 0.81     |
| 0.3312        | 1.1   | 100  | 0.3438          | 0.86     |
| 0.288         | 1.65  | 150  | 0.3476          | 0.84     |
| 0.2155        | 2.2   | 200  | 0.4957          | 0.81     |
| 0.1593        | 2.75  | 250  | 0.4748          | 0.81     |
| 0.1352        | 3.3   | 300  | 0.5133          | 0.8      |
| 0.0887        | 3.85  | 350  | 0.4520          | 0.86     |
| 0.0497        | 4.4   | 400  | 0.7308          | 0.82     |
| 0.0802        | 4.95  | 450  | 0.6633          | 0.84     |
| 0.0188        | 5.49  | 500  | 0.6727          | 0.85     |
| 0.0384        | 6.04  | 550  | 0.8719          | 0.85     |
| 0.0251        | 6.59  | 600  | 0.7503          | 0.86     |
| 0.0193        | 7.14  | 650  | 0.8141          | 0.84     |
| 0.0196        | 7.69  | 700  | 0.7246          | 0.86     |
| 0.014         | 8.24  | 750  | 0.8134          | 0.83     |
| 0.0155        | 8.79  | 800  | 0.7549          | 0.88     |
| 0.0104        | 9.34  | 850  | 0.7811          | 0.83     |
| 0.01          | 9.89  | 900  | 0.8459          | 0.83     |
| 0.004         | 10.44 | 950  | 0.7777          | 0.88     |
| 0.0007        | 10.99 | 1000 | 0.8015          | 0.87     |
| 0.0021        | 11.54 | 1050 | 0.7967          | 0.87     |
| 0.0009        | 12.09 | 1100 | 0.8019          | 0.88     |
| 0.0111        | 12.64 | 1150 | 0.8450          | 0.87     |
| 0.0003        | 13.19 | 1200 | 0.8463          | 0.84     |
| 0.0022        | 13.74 | 1250 | 0.8715          | 0.85     |
| 0.0039        | 14.29 | 1300 | 0.8378          | 0.83     |
| 0.0023        | 14.84 | 1350 | 0.8352          | 0.83     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1