---
base_model: CAMeL-Lab/bert-base-arabic-camelbert-msa
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: Monglish_Arabic_FAQ-V3
  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. -->

# Monglish_Arabic_FAQ-V3

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3059
- Accuracy: 0.9558
- F1: 0.9520
- Precision: 0.9674
- Recall: 0.9558

## 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: 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: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Validation Loss | Precision | Recall |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------------:|:---------:|:------:|
| 1.1065        | 1.0   | 226  | 0.8850   | 0.8681 | 1.0925          | 0.9284    | 0.8850 |
| 0.12          | 2.0   | 452  | 0.3676   | 0.9381 | 0.9392          | 0.9639    | 0.9381 |
| 0.0403        | 3.0   | 678  | 0.2427   | 0.9558 | 0.9562          | 0.9705    | 0.9558 |
| 0.0179        | 4.0   | 904  | 0.2722   | 0.9469 | 0.9443          | 0.9645    | 0.9469 |
| 0.0129        | 5.0   | 1130 | 0.2694   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0151        | 6.0   | 1356 | 0.2493   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0046        | 7.0   | 1582 | 0.2811   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0036        | 8.0   | 1808 | 0.2630   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0051        | 9.0   | 2034 | 0.2787   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0038        | 10.0  | 2260 | 0.2924   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0027        | 11.0  | 2486 | 0.3098   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0034        | 12.0  | 2712 | 0.3010   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0046        | 13.0  | 2938 | 0.3051   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0033        | 14.0  | 3164 | 0.3070   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |
| 0.0016        | 15.0  | 3390 | 0.3059   | 0.9558 | 0.9520          | 0.9674    | 0.9558 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1