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---
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license: mit
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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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- accuracy
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- f1
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model-index:
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- name: berturk-uncased-keyword-extractor
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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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# berturk-uncased-keyword-extractor
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This model is a fine-tuned version of [dbmdz/bert-base-turkish-uncased](https://huggingface.co/dbmdz/bert-base-turkish-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3931
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- Precision: 0.6631
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- Recall: 0.6728
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- Accuracy: 0.9188
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- F1: 0.6679
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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: 16
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- eval_batch_size: 16
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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: 8
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:------:|
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| 0.1779 | 1.0 | 1875 | 0.1862 | 0.6199 | 0.6356 | 0.9192 | 0.6276 |
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| 0.1327 | 2.0 | 3750 | 0.1890 | 0.6328 | 0.6917 | 0.9206 | 0.6610 |
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| 0.1008 | 3.0 | 5625 | 0.2188 | 0.6322 | 0.7037 | 0.9189 | 0.6660 |
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| 0.0755 | 4.0 | 7500 | 0.2539 | 0.6395 | 0.7030 | 0.9181 | 0.6697 |
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| 0.0574 | 5.0 | 9375 | 0.2882 | 0.6556 | 0.6868 | 0.9197 | 0.6709 |
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| 0.0433 | 6.0 | 11250 | 0.3425 | 0.6565 | 0.6851 | 0.9189 | 0.6705 |
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| 0.0352 | 7.0 | 13125 | 0.3703 | 0.6616 | 0.6776 | 0.9191 | 0.6695 |
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| 0.0288 | 8.0 | 15000 | 0.3931 | 0.6631 | 0.6728 | 0.9188 | 0.6679 |
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### Framework versions
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- Transformers 4.19.2
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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