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--- |
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license: mit |
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base_model: dbmdz/distilbert-base-turkish-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: acer_nitro_distilbert_turk |
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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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# acer_nitro_distilbert_turk |
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This model is a fine-tuned version of [dbmdz/distilbert-base-turkish-cased](https://huggingface.co/dbmdz/distilbert-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: 0.7724 |
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- F1: 0.7596 |
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- Roc Auc: 0.8506 |
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- Accuracy: 0.6386 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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 | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 166 | 0.6408 | 0.7330 | 0.8464 | 0.5904 | |
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| No log | 2.0 | 332 | 0.6674 | 0.7549 | 0.8434 | 0.6386 | |
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| No log | 3.0 | 498 | 0.7058 | 0.7573 | 0.8470 | 0.6145 | |
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| 0.3537 | 4.0 | 664 | 0.7887 | 0.7333 | 0.8358 | 0.6145 | |
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| 0.3537 | 5.0 | 830 | 0.8267 | 0.7586 | 0.8447 | 0.6265 | |
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| 0.3537 | 6.0 | 996 | 0.7217 | 0.7477 | 0.8491 | 0.6506 | |
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| 0.191 | 7.0 | 1162 | 0.7180 | 0.7593 | 0.8588 | 0.6506 | |
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| 0.191 | 8.0 | 1328 | 0.7742 | 0.7670 | 0.8531 | 0.6386 | |
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| 0.191 | 9.0 | 1494 | 0.7798 | 0.7560 | 0.8493 | 0.6265 | |
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| 0.1294 | 10.0 | 1660 | 0.7724 | 0.7596 | 0.8506 | 0.6386 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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