---
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: 2.1465
- Accuracy: 0.5
- F1: 0.4840
- Precision: 0.5908
- Recall: 0.5

## 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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 3.06          | 1.0   | 8    | 2.5319          | 0.1667   | 0.1604 | 0.2435    | 0.1667 |
| 2.4666        | 2.0   | 16   | 2.3235          | 0.4333   | 0.365  | 0.3833    | 0.4333 |
| 2.2624        | 3.0   | 24   | 2.1953          | 0.4667   | 0.4512 | 0.5442    | 0.4667 |
| 1.7783        | 4.0   | 32   | 2.1465          | 0.5      | 0.4840 | 0.5908    | 0.5    |
| 1.5082        | 5.0   | 40   | 2.1247          | 0.4667   | 0.4530 | 0.5917    | 0.4667 |


### Framework versions

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