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---
library_name: transformers
license: mit
base_model: bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: classifier-de
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# classifier-de
This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3460
- Accuracy: 0.8811
- Precision: 0.5353
- Recall: 0.2849
- F1: 0.3719
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2897 | 0.2569 | 500 | 0.3390 | 0.8773 | 0.5747 | 0.0282 | 0.0537 |
| 0.2437 | 0.5139 | 1000 | 0.3320 | 0.8789 | 0.5347 | 0.1568 | 0.2425 |
| 0.2292 | 0.7708 | 1500 | 0.3317 | 0.8826 | 0.5760 | 0.1901 | 0.2859 |
| 0.1915 | 1.0277 | 2000 | 0.3557 | 0.8820 | 0.5583 | 0.2164 | 0.3119 |
| 0.2146 | 1.2847 | 2500 | 0.3390 | 0.8837 | 0.5757 | 0.2250 | 0.3236 |
| 0.2222 | 1.5416 | 3000 | 0.3298 | 0.8811 | 0.5358 | 0.2819 | 0.3694 |
| 0.1861 | 1.7986 | 3500 | 0.3338 | 0.8823 | 0.5501 | 0.2620 | 0.3549 |
| 0.1789 | 2.0555 | 4000 | 0.3460 | 0.8811 | 0.5353 | 0.2849 | 0.3719 |
| 0.1739 | 2.3124 | 4500 | 0.3614 | 0.8850 | 0.5863 | 0.2368 | 0.3373 |
| 0.1899 | 2.5694 | 5000 | 0.3487 | 0.8844 | 0.5716 | 0.2578 | 0.3554 |
| 0.1692 | 2.8263 | 5500 | 0.3484 | 0.8847 | 0.5728 | 0.2653 | 0.3626 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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