End of training
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README.md
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---
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library_name: transformers
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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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- 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: best_model_categorize
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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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# best_model_categorize
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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: 0.0431
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- Precision: 0.6642
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- Recall: 0.7093
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- F1: 0.6860
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- Accuracy: 0.9857
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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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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| No log | 1.0 | 309 | 0.2587 | 0.1656 | 0.2316 | 0.1931 | 0.9131 |
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| 0.3346 | 2.0 | 618 | 0.1543 | 0.3189 | 0.4404 | 0.3700 | 0.9524 |
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| 0.3346 | 3.0 | 927 | 0.0821 | 0.4876 | 0.5654 | 0.5236 | 0.9732 |
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| 0.1746 | 4.0 | 1236 | 0.0551 | 0.6009 | 0.6621 | 0.6300 | 0.9816 |
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| 0.083 | 5.0 | 1545 | 0.0431 | 0.6642 | 0.7093 | 0.6860 | 0.9857 |
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### Framework versions
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- Transformers 4.48.2
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- Pytorch 2.6.0+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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