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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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language:
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- tr
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metrics:
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- accuracy
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- recall
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- f1
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library_name: transformers
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pipeline_tag: text-classification
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model-index:
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- name: deprem_v12
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results:
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- task:
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type: text-classification
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dataset:
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type: deprem_private_dataset_v1_2
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name: deprem_private_dataset_v1_2
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metrics:
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- type: recall
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value: 0.82
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verified: false
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- type: f1
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value: 0.76
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verified: false
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widget:
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- text: >-
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acil acil acil antakyadan istanbula gitmek için antakya expoya ulaşmaya çalışan 19 kişilik bir aile için şehir içi ulaşım desteği istiyoruz. dışardalar üşüyorlar.iletebileceğiniz numaraları bekliyorum
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example_title: Örnek
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---
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## Eval Results
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```
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precision recall f1-score support
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Alakasiz 0.87 0.91 0.89 734
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Barinma 0.79 0.89 0.84 207
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Elektronik 0.69 0.83 0.75 130
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Giysi 0.71 0.81 0.76 94
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Kurtarma 0.82 0.85 0.83 362
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Lojistik 0.57 0.67 0.62 112
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Saglik 0.68 0.85 0.75 108
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Su 0.56 0.76 0.64 78
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Yagma 0.60 0.77 0.68 31
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Yemek 0.71 0.89 0.79 117
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micro avg 0.77 0.86 0.81 1973
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macro avg 0.70 0.82 0.76 1973
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weighted avg 0.78 0.86 0.82 1973
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samples avg 0.83 0.88 0.84 1973
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```
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## Threshold:
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- **Best Threshold:** 0.40
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```python
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{'per_device_train_batch_size': 32,
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'per_device_eval_batch_size': 32,
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'learning_rate': 5.8679699888213376e-05,
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'weight_decay': 0.03530961718117487,
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'num_train_epochs': 4,
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'lr_scheduler_type': 'cosine',
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'warmup_steps': 40,
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'seed': 42,
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'fp16': True,
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'load_best_model_at_end': True,
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'metric_for_best_model': 'macro f1',
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'greater_is_better': True,
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```
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## Class Loss Weights
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- Same as Anıl's approach.
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