---
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