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--- |
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library_name: transformers |
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license: mit |
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base_model: akdeniz27/bert-base-turkish-cased-ner |
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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-ner-finetuned-ner |
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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-ner-finetuned-ner |
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This model is a fine-tuned version of [akdeniz27/bert-base-turkish-cased-ner](https://huggingface.co/akdeniz27/bert-base-turkish-cased-ner) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2379 |
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- Precision: 0.9707 |
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- Recall: 0.9708 |
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- F1: 0.9708 |
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- Accuracy: 0.9729 |
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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: 1e-05 |
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- train_batch_size: 6 |
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- eval_batch_size: 6 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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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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| 0.1631 | 1.0 | 3334 | 0.1465 | 0.9620 | 0.9627 | 0.9624 | 0.9651 | |
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| 0.1162 | 2.0 | 6668 | 0.1524 | 0.9659 | 0.9655 | 0.9657 | 0.9683 | |
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| 0.0938 | 3.0 | 10002 | 0.1452 | 0.9686 | 0.9691 | 0.9688 | 0.9712 | |
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| 0.048 | 4.0 | 13336 | 0.1734 | 0.9698 | 0.9697 | 0.9698 | 0.9719 | |
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| 0.0359 | 5.0 | 16670 | 0.1810 | 0.9701 | 0.9703 | 0.9702 | 0.9723 | |
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| 0.0274 | 6.0 | 20004 | 0.1941 | 0.9713 | 0.9713 | 0.9713 | 0.9734 | |
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| 0.0187 | 7.0 | 23338 | 0.2185 | 0.9700 | 0.9700 | 0.9700 | 0.9722 | |
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| 0.0229 | 8.0 | 26672 | 0.2265 | 0.9706 | 0.9707 | 0.9707 | 0.9728 | |
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| 0.015 | 9.0 | 30006 | 0.2325 | 0.9706 | 0.9705 | 0.9706 | 0.9729 | |
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| 0.009 | 10.0 | 33340 | 0.2379 | 0.9707 | 0.9708 | 0.9708 | 0.9729 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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