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--- |
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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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- accuracy |
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model-index: |
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- name: results |
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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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# results |
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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: 0.1216 |
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- Accuracy: 0.9767 |
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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: 16 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.0625 | 0.12 | 200 | 0.3592 | 0.8799 | |
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| 0.2277 | 0.25 | 400 | 0.1771 | 0.9473 | |
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| 0.202 | 0.37 | 600 | 0.1594 | 0.9602 | |
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| 0.1711 | 0.5 | 800 | 0.1588 | 0.9612 | |
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| 0.1532 | 0.62 | 1000 | 0.1764 | 0.9525 | |
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| 0.1508 | 0.75 | 1200 | 0.1482 | 0.9627 | |
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| 0.1441 | 0.87 | 1400 | 0.1102 | 0.9719 | |
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| 0.1128 | 0.99 | 1600 | 0.1284 | 0.9686 | |
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| 0.07 | 1.12 | 1800 | 0.1321 | 0.9686 | |
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| 0.0812 | 1.24 | 2000 | 0.1365 | 0.9706 | |
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| 0.0858 | 1.37 | 2200 | 0.1046 | 0.9719 | |
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| 0.0636 | 1.49 | 2400 | 0.1263 | 0.9709 | |
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| 0.0861 | 1.62 | 2600 | 0.1081 | 0.9742 | |
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| 0.0623 | 1.74 | 2800 | 0.1148 | 0.9748 | |
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| 0.082 | 1.86 | 3000 | 0.0877 | 0.9778 | |
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| 0.0456 | 1.99 | 3200 | 0.1167 | 0.9751 | |
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| 0.0277 | 2.11 | 3400 | 0.1147 | 0.9759 | |
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| 0.0205 | 2.24 | 3600 | 0.1247 | 0.9753 | |
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| 0.0167 | 2.36 | 3800 | 0.1188 | 0.9776 | |
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| 0.0185 | 2.49 | 4000 | 0.1362 | 0.9762 | |
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| 0.0156 | 2.61 | 4200 | 0.1254 | 0.9762 | |
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| 0.0273 | 2.73 | 4400 | 0.1230 | 0.9768 | |
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| 0.019 | 2.86 | 4600 | 0.1245 | 0.9764 | |
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| 0.0102 | 2.98 | 4800 | 0.1216 | 0.9767 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.14.1 |
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