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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: irem_5e-05_4_10_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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# irem_5e-05_4_10_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: 0.8459 |
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- Precision: 0.2556 |
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- Recall: 0.2403 |
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- F1: 0.2477 |
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- Accuracy: 0.8883 |
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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: 4 |
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- eval_batch_size: 4 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| 0.2701 | 1.0 | 672 | 0.1902 | 0.125 | 0.0926 | 0.1064 | 0.9460 | |
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| 0.2016 | 2.0 | 1344 | 0.1750 | 0.1173 | 0.1759 | 0.1407 | 0.9453 | |
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| 0.1195 | 3.0 | 2016 | 0.2107 | 0.1880 | 0.2315 | 0.2075 | 0.9476 | |
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| 0.0776 | 4.0 | 2688 | 0.2238 | 0.1397 | 0.1759 | 0.1557 | 0.9473 | |
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| 0.0314 | 5.0 | 3360 | 0.2438 | 0.2057 | 0.2685 | 0.2329 | 0.9506 | |
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| 0.022 | 6.0 | 4032 | 0.3185 | 0.2231 | 0.25 | 0.2358 | 0.9498 | |
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| 0.0165 | 7.0 | 4704 | 0.3448 | 0.2177 | 0.25 | 0.2328 | 0.9494 | |
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| 0.0078 | 8.0 | 5376 | 0.3405 | 0.2308 | 0.2778 | 0.2521 | 0.9501 | |
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| 0.0035 | 9.0 | 6048 | 0.3445 | 0.2121 | 0.2593 | 0.2333 | 0.9484 | |
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| 0.0035 | 10.0 | 6720 | 0.3680 | 0.2273 | 0.2778 | 0.25 | 0.9489 | |
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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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