README.md

---
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 |     1.51721  |    1.50726  |         0.670392 |        0.685955 | 0.647908 |    0.695828 | 0.670392 |
|       2 |     0.827407 |    0.804686 |         0.779283 |        0.790449 | 0.779526 |    0.787574 | 0.779283 |
|       3 |     0.624589 |    0.617633 |         0.815747 |        0.823596 | 0.815815 |    0.818754 | 0.815747 |
|       4 |     0.577044 |    0.593563 |         0.822927 |        0.821348 | 0.824907 |    0.835161 | 0.822927 |
|       5 |     0.504094 |    0.535676 |         0.839036 |        0.834831 | 0.839583 |    0.842469 | 0.839036 |
|       6 |     0.46799  |    0.520281 |         0.849213 |        0.835955 | 0.850536 |    0.855303 | 0.849213 |
|       7 |     0.445317 |    0.510596 |         0.854708 |        0.840449 | 0.855552 |    0.858046 | 0.854708 |
|       8 |     0.428012 |    0.501261 |         0.858142 |        0.842135 | 0.859003 |    0.862191 | 0.858142 |
|       9 |     0.412287 |    0.491676 |         0.864635 |        0.848315 | 0.865268 |    0.868648 | 0.864635 |
|      10 |     0.400929 |    0.497091 |         0.868194 |        0.847753 | 0.8693   |    0.872337 | 0.868194 |
|      11 |     0.395328 |    0.506237 |         0.868319 |        0.840449 | 0.870433 |    0.87781  | 0.868319 |
|      12 |     0.378038 |    0.483877 |         0.874813 |        0.847191 | 0.875232 |    0.877259 | 0.874813 |
|      13 |     0.3727   |    0.488525 |         0.874313 |        0.841573 | 0.875207 |    0.878724 | 0.874313 |
|      14 |     0.366197 |    0.482607 |         0.878059 |        0.85     | 0.878635 |    0.880364 | 0.878059 |
|      15 |     0.365844 |    0.485294 |         0.878247 |        0.851124 | 0.879    |    0.88123  | 0.878247 |

## 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%})")