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--- |
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library_name: transformers |
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license: mit |
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base_model: dbmdz/bert-base-turkish-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-base-turkish-cased_hate_span_detection_final |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-turkish-cased_hate_span_detection_final |
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This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4984 |
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- Precision: 0.3858 |
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- Recall: 0.4441 |
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- F1: 0.4129 |
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- Accuracy: 0.9018 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 62 | 0.2853 | 0.3103 | 0.3648 | 0.3354 | 0.8888 | |
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| 0.3754 | 2.0 | 124 | 0.2557 | 0.3672 | 0.4783 | 0.4155 | 0.8958 | |
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| 0.3754 | 3.0 | 186 | 0.2704 | 0.3920 | 0.4983 | 0.4388 | 0.8972 | |
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| 0.1772 | 4.0 | 248 | 0.2925 | 0.4431 | 0.5028 | 0.4711 | 0.9023 | |
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| 0.096 | 5.0 | 310 | 0.3442 | 0.4179 | 0.5184 | 0.4628 | 0.8984 | |
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| 0.096 | 6.0 | 372 | 0.3654 | 0.4395 | 0.5295 | 0.4803 | 0.9018 | |
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| 0.0607 | 7.0 | 434 | 0.3743 | 0.4698 | 0.5184 | 0.4929 | 0.9063 | |
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| 0.0607 | 8.0 | 496 | 0.4196 | 0.4614 | 0.5250 | 0.4912 | 0.9059 | |
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| 0.0429 | 9.0 | 558 | 0.4325 | 0.4472 | 0.5417 | 0.4899 | 0.9025 | |
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| 0.0298 | 10.0 | 620 | 0.4474 | 0.4609 | 0.5373 | 0.4961 | 0.9040 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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