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README.md
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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-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-keyword-extractor
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4306
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- Precision: 0.6770
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- Recall: 0.6899
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- Accuracy: 0.9169
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- F1: 0.6834
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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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| 0.1845 | 1.0 | 1875 | 0.1964 | 0.6380 | 0.6743 | 0.9164 | 0.6557 |
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| 0.1338 | 2.0 | 3750 | 0.2023 | 0.6407 | 0.7081 | 0.9169 | 0.6727 |
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| 0.0978 | 3.0 | 5625 | 0.2315 | 0.6434 | 0.7309 | 0.9159 | 0.6844 |
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| 0.0742 | 4.0 | 7500 | 0.2746 | 0.6592 | 0.7144 | 0.9158 | 0.6857 |
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| 0.0541 | 5.0 | 9375 | 0.3290 | 0.6700 | 0.6880 | 0.9161 | 0.6789 |
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| 0.0426 | 6.0 | 11250 | 0.3608 | 0.6789 | 0.6860 | 0.9171 | 0.6824 |
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| 0.0332 | 7.0 | 13125 | 0.4075 | 0.6769 | 0.6924 | 0.9168 | 0.6845 |
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| 0.027 | 8.0 | 15000 | 0.4306 | 0.6770 | 0.6899 | 0.9169 | 0.6834 |
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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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