---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: arabic-dialect-model
  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. -->

# arabic-dialect-model

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-msa](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7129
- Accuracy: 0.1778
- F1: 0.1297
- Precision: 0.1777
- Recall: 0.1778

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 3.0984        | 1.0   | 16   | 3.0297          | 0.0444   | 0.05   | 0.0593    | 0.0444 |
| 2.9882        | 2.0   | 32   | 2.9796          | 0.0889   | 0.0660 | 0.0526    | 0.0889 |
| 2.904         | 3.0   | 48   | 2.9029          | 0.1111   | 0.0577 | 0.0399    | 0.1111 |
| 2.7871        | 4.0   | 64   | 2.8040          | 0.1778   | 0.1057 | 0.1370    | 0.1778 |
| 2.6578        | 5.0   | 80   | 2.7129          | 0.1778   | 0.1297 | 0.1777    | 0.1778 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cpu
- Datasets 2.13.0
- Tokenizers 0.13.3