---
license: mit
base_model: dbmdz/bert-base-german-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-german-uncased
  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. -->

# bert-base-german-uncased

This model is a fine-tuned version of [dbmdz/bert-base-german-uncased](https://huggingface.co/dbmdz/bert-base-german-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5523
- F1: 0.4333

## 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: 2e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6943        | 1.0   | 189  | 0.6839          | 0.08   |
| 0.6718        | 2.0   | 378  | 0.6603          | 0.0339 |
| 0.66          | 3.0   | 567  | 0.6508          | 0.0476 |
| 0.6568        | 4.0   | 756  | 0.6457          | 0.05   |
| 0.6638        | 5.0   | 945  | 0.6439          | 0.0513 |
| 0.6552        | 6.0   | 1134 | 0.6387          | 0.0556 |
| 0.6709        | 7.0   | 1323 | 0.6386          | 0.0556 |
| 0.6541        | 8.0   | 1512 | 0.6369          | 0.0556 |
| 0.6644        | 9.0   | 1701 | 0.6434          | 0.0    |
| 0.6601        | 10.0  | 1890 | 0.6432          | 0.0    |
| 0.6558        | 11.0  | 2079 | 0.6421          | 0.0    |
| 0.6548        | 12.0  | 2268 | 0.6398          | 0.0    |
| 0.6593        | 13.0  | 2457 | 0.6401          | 0.0    |
| 0.6502        | 14.0  | 2646 | 0.6366          | 0.0    |
| 0.6457        | 15.0  | 2835 | 0.6292          | 0.0541 |
| 0.6478        | 16.0  | 3024 | 0.6267          | 0.0541 |
| 0.6378        | 17.0  | 3213 | 0.6311          | 0.0    |
| 0.6325        | 18.0  | 3402 | 0.6279          | 0.0    |
| 0.6467        | 19.0  | 3591 | 0.6253          | 0.0    |
| 0.6338        | 20.0  | 3780 | 0.6227          | 0.0    |
| 0.6281        | 21.0  | 3969 | 0.6194          | 0.0    |
| 0.6205        | 22.0  | 4158 | 0.6155          | 0.0    |
| 0.6288        | 23.0  | 4347 | 0.6113          | 0.0    |
| 0.6178        | 24.0  | 4536 | 0.6081          | 0.0976 |
| 0.6221        | 25.0  | 4725 | 0.6049          | 0.1778 |
| 0.612         | 26.0  | 4914 | 0.6011          | 0.25   |
| 0.6052        | 27.0  | 5103 | 0.5971          | 0.25   |
| 0.5997        | 28.0  | 5292 | 0.5925          | 0.2553 |
| 0.603         | 29.0  | 5481 | 0.5895          | 0.3265 |
| 0.5973        | 30.0  | 5670 | 0.5856          | 0.3200 |
| 0.594         | 31.0  | 5859 | 0.5821          | 0.3200 |
| 0.5825        | 32.0  | 6048 | 0.5786          | 0.3529 |
| 0.5787        | 33.0  | 6237 | 0.5753          | 0.3929 |
| 0.5848        | 34.0  | 6426 | 0.5724          | 0.3929 |
| 0.5703        | 35.0  | 6615 | 0.5698          | 0.4000 |
| 0.584         | 36.0  | 6804 | 0.5673          | 0.3929 |
| 0.5668        | 37.0  | 6993 | 0.5648          | 0.3860 |
| 0.5624        | 38.0  | 7182 | 0.5629          | 0.3860 |
| 0.5793        | 39.0  | 7371 | 0.5611          | 0.4138 |
| 0.5555        | 40.0  | 7560 | 0.5593          | 0.3860 |
| 0.5664        | 41.0  | 7749 | 0.5579          | 0.4407 |
| 0.553         | 42.0  | 7938 | 0.5566          | 0.4483 |
| 0.5597        | 43.0  | 8127 | 0.5555          | 0.4483 |
| 0.5555        | 44.0  | 8316 | 0.5546          | 0.4407 |
| 0.5589        | 45.0  | 8505 | 0.5538          | 0.4333 |
| 0.5578        | 46.0  | 8694 | 0.5531          | 0.4333 |
| 0.5499        | 47.0  | 8883 | 0.5528          | 0.4333 |
| 0.5434        | 48.0  | 9072 | 0.5524          | 0.4333 |
| 0.5607        | 49.0  | 9261 | 0.5523          | 0.4333 |
| 0.5478        | 50.0  | 9450 | 0.5523          | 0.4333 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3