---
language: ar
license: apache-2.0
library_name: peft
base_model: UBC-NLP/MARBERT
tags:
- arabic
- dialect-classification
- lora
---

# HammaLoRAMarBert

Advanced Arabic Dialect Classification Model with Complete Training Metrics

![Training Metrics](training_metrics.png)

## Full Training History

|   epoch |   train_loss |   eval_loss |   train_accuracy |   eval_accuracy |       f1 |   precision |   recall |
|--------:|-------------:|------------:|-----------------:|----------------:|---------:|------------:|---------:|
|       1 |     1.01756  |    1.0054   |         0.70748  |        0.717978 | 0.693725 |    0.706778 | 0.70748  |
|       2 |     0.762952 |    0.75223  |         0.771853 |        0.78764  | 0.771604 |    0.778861 | 0.771853 |
|       3 |     0.650689 |    0.648891 |         0.796329 |        0.803371 | 0.797666 |    0.801681 | 0.796329 |
|       4 |     0.622925 |    0.626332 |         0.801449 |        0.811798 | 0.801765 |    0.80837  | 0.801449 |
|       5 |     0.576898 |    0.588152 |         0.809815 |        0.812921 | 0.810793 |    0.814344 | 0.809815 |
|       6 |     0.567929 |    0.60128  |         0.814623 |        0.810674 | 0.816486 |    0.823517 | 0.814623 |
|       7 |     0.556496 |    0.58585  |         0.818244 |        0.820225 | 0.818915 |    0.822701 | 0.818244 |
|       8 |     0.54978  |    0.592384 |         0.821054 |        0.820225 | 0.82197  |    0.82844  | 0.821054 |
|       9 |     0.543711 |    0.587352 |         0.824301 |        0.816854 | 0.826151 |    0.83428  | 0.824301 |
|      10 |     0.51674  |    0.565089 |         0.830607 |        0.818539 | 0.831944 |    0.83726  | 0.830607 |
|      11 |     0.520477 |    0.580509 |         0.830669 |        0.819663 | 0.832265 |    0.837997 | 0.830669 |
|      12 |     0.507471 |    0.563466 |         0.833729 |        0.82809  | 0.834758 |    0.839029 | 0.833729 |
|      13 |     0.498436 |    0.557207 |         0.834603 |        0.825281 | 0.835891 |    0.840618 | 0.834603 |
|      14 |     0.496213 |    0.551106 |         0.836289 |        0.828652 | 0.837213 |    0.840592 | 0.836289 |
|      15 |     0.493182 |    0.549526 |         0.836414 |        0.826404 | 0.837405 |    0.840693 | 0.836414 |

## Label Mapping:

{0: 'Egypt', 1: 'Iraq', 2: 'Lebanon', 3: 'Morocco', 4: 'Saudi_Arabia', 5: 'Sudan', 6: 'Tunisia'}

## USAGE Example:
```python
from transformers import pipeline

classifier = pipeline(
    "text-classification",
    model="Hamma-16/HammaLoRAMarBert",
    device="cuda" if torch.cuda.is_available() else "cpu"
)

sample_text = "شلونك اليوم؟"
result = classifier(sample_text)
print(f"Text: {sample_text}")
print(f"Predicted: {result[0]['label']} (confidence: {result[0]['score']:.1%})")