---
license: apache-2.0
language:
  - tr
tags:
  - deprem-clf-v1
metrics:
  - accuracy
  - recall
  - f1
library_name: transformers
pipeline_tag: text-classification
model-index:
  - name: deprem_v12
    results:
      - task:
          type: text-classification
        dataset:
          type: deprem_private_dataset_v1_2
          name: deprem_private_dataset_v1_2
        metrics:
          - type: recall
            value: 0.75
            verified: false
          - type: f1
            value: 0.75
            verified: false
widget:
  - text: >-
      HATAY DEFNE İLÇESİNE yardımlar gitmiyor Özellikle çadıra battaniyeye yiyeceğe ihtiyaç var. Antakyanın dışında olduğu için tüm yardimlar 
      İSKENDERUNA ANTAKYAYA gidiyor. Bu bölgeye gitmiyor..DEFNE İLÇESİNE GİDECEK ERZAK Çadır yardımlarını
    example_title: Örnek
---
**Train-Test Set:** "intent-multilabel-v1-2.zip"

**Model:** "dbmdz/bert-base-turkish-cased"

## Tokenizer Params
```
max_length=128
padding="max_length"
truncation=True
```

## Training Params
```
evaluation_strategy = "epoch"
save_strategy = "epoch"
per_device_train_batch_size = 16
per_device_eval_batch_size = 16
num_train_epochs = 4
load_best_model_at_end = True
```

## Train-Val Splitting Configuration
```
train_test_split(df_train,
                 test_size=0.1,
                 random_state=1111)
```

## Class Loss Weights
- **Alakasiz:** 1.0
- **Barinma:** 1.5167249178108022
- **Elektronik:** 1.7547338578655642
- **Giysi:** 1.9610520059358458
- **Kurtarma:** 1.269341370129623
- **Lojistik:** 1.8684086209021484
- **Saglik:** 1.8019018017117145
- **Su:** 2.110648663094536
- **Yagma:** 3.081208739200435
- **Yemek:** 1.7994815143101963
 
## Training Log (Class-Scaled)
```
Epoch	Training Loss	Validation Loss
1	    No log	        0.216295
2	    0.260000	    0.171498
3	    0.142700	    0.175608
4	    0.142700	    0.169851
```

## Threshold Optimization
- **Best Threshold:** 0.15
- **F1 @ Threshold:** 0.7503

## Eval Results
```
              precision    recall  f1-score   support

    Alakasiz       0.91      0.87      0.89       734
     Barinma       0.85      0.81      0.83       207
  Elektronik       0.72      0.78      0.75       130
       Giysi       0.73      0.67      0.70        94
    Kurtarma       0.86      0.81      0.83       362
    Lojistik       0.68      0.56      0.62       112
      Saglik       0.72      0.81      0.76       108
          Su       0.61      0.69      0.65        78
       Yagma       0.67      0.65      0.66        31
       Yemek       0.79      0.85      0.82       117

   micro avg       0.82      0.81      0.81      1973
   macro avg       0.75      0.75      0.75      1973
weighted avg       0.83      0.81      0.81      1973
 samples avg       0.84      0.84      0.83      1973
```