---
license: mit
base_model: bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Misinformation-Covid-LowLearningRatebert-base-german-cased
  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. -->

# Misinformation-Covid-LowLearningRatebert-base-german-cased

This model is a fine-tuned version of [bert-base-german-cased](https://huggingface.co/bert-base-german-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5151
- F1: 0.3793

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6534        | 1.0   | 189  | 0.6298          | 0.1000 |
| 0.6467        | 2.0   | 378  | 0.6222          | 0.1379 |
| 0.6302        | 3.0   | 567  | 0.6121          | 0.0784 |
| 0.6259        | 4.0   | 756  | 0.6042          | 0.0870 |
| 0.6255        | 5.0   | 945  | 0.5987          | 0.0870 |
| 0.6091        | 6.0   | 1134 | 0.5922          | 0.0909 |
| 0.6237        | 7.0   | 1323 | 0.5881          | 0.1224 |
| 0.6019        | 8.0   | 1512 | 0.5826          | 0.1277 |
| 0.6038        | 9.0   | 1701 | 0.5779          | 0.2    |
| 0.5996        | 10.0  | 1890 | 0.5730          | 0.1961 |
| 0.5858        | 11.0  | 2079 | 0.5678          | 0.2353 |
| 0.5794        | 12.0  | 2268 | 0.5636          | 0.24   |
| 0.5806        | 13.0  | 2457 | 0.5587          | 0.2264 |
| 0.5586        | 14.0  | 2646 | 0.5548          | 0.24   |
| 0.5682        | 15.0  | 2835 | 0.5514          | 0.24   |
| 0.5631        | 16.0  | 3024 | 0.5471          | 0.2353 |
| 0.5603        | 17.0  | 3213 | 0.5425          | 0.2593 |
| 0.5437        | 18.0  | 3402 | 0.5393          | 0.2593 |
| 0.5439        | 19.0  | 3591 | 0.5368          | 0.2642 |
| 0.547         | 20.0  | 3780 | 0.5329          | 0.2909 |
| 0.5408        | 21.0  | 3969 | 0.5297          | 0.3158 |
| 0.5327        | 22.0  | 4158 | 0.5270          | 0.3158 |
| 0.5194        | 23.0  | 4347 | 0.5256          | 0.3214 |
| 0.5206        | 24.0  | 4536 | 0.5227          | 0.3214 |
| 0.516         | 25.0  | 4725 | 0.5205          | 0.3214 |
| 0.5103        | 26.0  | 4914 | 0.5191          | 0.3214 |
| 0.5037        | 27.0  | 5103 | 0.5172          | 0.3214 |
| 0.4974        | 28.0  | 5292 | 0.5180          | 0.3214 |
| 0.5116        | 29.0  | 5481 | 0.5156          | 0.3214 |
| 0.5006        | 30.0  | 5670 | 0.5150          | 0.3214 |
| 0.509         | 31.0  | 5859 | 0.5141          | 0.3214 |
| 0.4832        | 32.0  | 6048 | 0.5150          | 0.3273 |
| 0.4877        | 33.0  | 6237 | 0.5133          | 0.3214 |
| 0.49          | 34.0  | 6426 | 0.5131          | 0.3158 |
| 0.4827        | 35.0  | 6615 | 0.5143          | 0.3214 |
| 0.4986        | 36.0  | 6804 | 0.5125          | 0.3214 |
| 0.4794        | 37.0  | 6993 | 0.5131          | 0.3793 |
| 0.4809        | 38.0  | 7182 | 0.5137          | 0.3793 |
| 0.4929        | 39.0  | 7371 | 0.5114          | 0.3793 |
| 0.465         | 40.0  | 7560 | 0.5135          | 0.3793 |
| 0.4867        | 41.0  | 7749 | 0.5121          | 0.3793 |
| 0.4685        | 42.0  | 7938 | 0.5129          | 0.3793 |
| 0.4643        | 43.0  | 8127 | 0.5142          | 0.3793 |
| 0.4804        | 44.0  | 8316 | 0.5144          | 0.3793 |
| 0.4779        | 45.0  | 8505 | 0.5141          | 0.3793 |
| 0.4701        | 46.0  | 8694 | 0.5139          | 0.3793 |
| 0.4619        | 47.0  | 8883 | 0.5146          | 0.3793 |
| 0.4558        | 48.0  | 9072 | 0.5151          | 0.3793 |
| 0.4824        | 49.0  | 9261 | 0.5152          | 0.3793 |
| 0.4758        | 50.0  | 9450 | 0.5151          | 0.3793 |


### Framework versions

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