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---
license: apache-2.0
language:
  - tr
metrics:
  - accuracy
  - recall
  - f1

library_name: transformers
pipeline_tag: text-classification
model-index:
  - name: deprem_v13
    results:
      - task:
          type: text-classification
        dataset:
          type: deprem_private_dataset_v13
          name: deprem_private_dataset_v13
        metrics:
          - type: recall
            value: 0.85
            verified: false
          - type: f1
            value: 0.84
            verified: false
widget:
  - text: >-
      acil acil acil antakyadan istanbula gitmek için antakya expoya ulaşmaya çalışan 9 kişilik bir aile için şehir içi ulaşım desteği istiyoruz. dışardalar üşüyorlar.iletebileceğiniz numaraları bekliyorum 
    example_title: Örnek
---

## Eval Results
```
                  precision    recall  f1-score   support
        Lojistik       0.81      0.79      0.80        38
Elektrik Kaynagi       0.73      0.91      0.81        56
  Arama Ekipmani       0.79      0.74      0.76       128
          Cenaze       1.00      0.50      0.67         2
           Giysi       0.82      0.96      0.89       138
  Enkaz Kaldirma       0.94      0.94      0.94       919
          Isinma       0.84      0.89      0.86       185
         Barınma       0.96      0.96      0.96       483
         Tuvalet       0.67      0.80      0.73        10
              Su       0.83      0.87      0.85        67
           Yemek       0.89      0.96      0.92       202
          Saglik       0.80      0.88      0.83       104
        Alakasiz       0.90      0.82      0.86       377

       micro avg       0.89      0.91      0.90      2709
       macro avg       0.84      0.85      0.84      2709
    weighted avg       0.90      0.91      0.90      2709
     samples avg       0.91      0.92      0.91      2709
```

## Threshold:
- **Best Threshold:** 0.53

## Class Loss Weights

```python
    [3.017203135650159,
     2.4823691788825464,
     1.941736822154725,
     6.172646581418988,
     1.8759436445637834,
     1.0,
     1.75011143349181,
     1.2730236191357969,
     4.849237178079731,
     2.4857419672410703,
     1.6324480531290084,
     2.0033774839735035,
     1.3688883733394182]
```