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--- |
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library_name: transformers |
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license: mit |
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base_model: bert-base-german-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: classifier-de |
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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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# classifier-de |
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This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3460 |
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- Accuracy: 0.8811 |
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- Precision: 0.5353 |
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- Recall: 0.2849 |
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- F1: 0.3719 |
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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: 1.5e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.2897 | 0.2569 | 500 | 0.3390 | 0.8773 | 0.5747 | 0.0282 | 0.0537 | |
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| 0.2437 | 0.5139 | 1000 | 0.3320 | 0.8789 | 0.5347 | 0.1568 | 0.2425 | |
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| 0.2292 | 0.7708 | 1500 | 0.3317 | 0.8826 | 0.5760 | 0.1901 | 0.2859 | |
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| 0.1915 | 1.0277 | 2000 | 0.3557 | 0.8820 | 0.5583 | 0.2164 | 0.3119 | |
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| 0.2146 | 1.2847 | 2500 | 0.3390 | 0.8837 | 0.5757 | 0.2250 | 0.3236 | |
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| 0.2222 | 1.5416 | 3000 | 0.3298 | 0.8811 | 0.5358 | 0.2819 | 0.3694 | |
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| 0.1861 | 1.7986 | 3500 | 0.3338 | 0.8823 | 0.5501 | 0.2620 | 0.3549 | |
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| 0.1789 | 2.0555 | 4000 | 0.3460 | 0.8811 | 0.5353 | 0.2849 | 0.3719 | |
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| 0.1739 | 2.3124 | 4500 | 0.3614 | 0.8850 | 0.5863 | 0.2368 | 0.3373 | |
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| 0.1899 | 2.5694 | 5000 | 0.3487 | 0.8844 | 0.5716 | 0.2578 | 0.3554 | |
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| 0.1692 | 2.8263 | 5500 | 0.3484 | 0.8847 | 0.5728 | 0.2653 | 0.3626 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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