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 |     1.23777  |    1.22883  |         0.696741 |        0.706742 | 0.679064 |    0.704547 | 0.696741 |
|       2 |     0.740169 |    0.733708 |         0.790397 |        0.800562 | 0.791608 |    0.797789 | 0.790397 |
|       3 |     0.601572 |    0.617834 |         0.818182 |        0.821348 | 0.819564 |    0.824729 | 0.818182 |
|       4 |     0.562756 |    0.585901 |         0.824363 |        0.816292 | 0.825464 |    0.835567 | 0.824363 |
|       5 |     0.497183 |    0.534541 |         0.839411 |        0.832022 | 0.839956 |    0.842141 | 0.839411 |
|       6 |     0.467484 |    0.529349 |         0.848964 |        0.830899 | 0.850348 |    0.855113 | 0.848964 |
|       7 |     0.447877 |    0.52692  |         0.851773 |        0.832022 | 0.852826 |    0.857268 | 0.851773 |
|       8 |     0.44038  |    0.525875 |         0.854021 |        0.830337 | 0.855092 |    0.860913 | 0.854021 |
|       9 |     0.416875 |    0.513681 |         0.863886 |        0.835955 | 0.865207 |    0.870201 | 0.863886 |
|      10 |     0.397198 |    0.498091 |         0.868506 |        0.839888 | 0.869502 |    0.872867 | 0.868506 |
|      11 |     0.396181 |    0.509205 |         0.86757  |        0.835955 | 0.869238 |    0.875968 | 0.86757  |
|      12 |     0.38368  |    0.494237 |         0.873064 |        0.838764 | 0.87361  |    0.875448 | 0.873064 |
|      13 |     0.377543 |    0.496908 |         0.874001 |        0.83764  | 0.874749 |    0.877947 | 0.874001 |
|      14 |     0.371016 |    0.491708 |         0.877435 |        0.841573 | 0.878057 |    0.880101 | 0.877435 |
|      15 |     0.370049 |    0.493832 |         0.877872 |        0.840449 | 0.878651 |    0.881198 | 0.877872 |

## 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%})")