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# Misinformation-Covid-bert-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: 0.7182
- F1: 0.3333

## 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-06
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6609        | 1.0   | 189  | 0.6062          | 0.0    |
| 0.6168        | 2.0   | 378  | 0.5649          | 0.1818 |
| 0.5638        | 3.0   | 567  | 0.5665          | 0.1818 |
| 0.5382        | 4.0   | 756  | 0.5790          | 0.2128 |
| 0.5399        | 5.0   | 945  | 0.5459          | 0.3284 |
| 0.4745        | 6.0   | 1134 | 0.7525          | 0.3265 |
| 0.5061        | 7.0   | 1323 | 0.6379          | 0.3529 |
| 0.377         | 8.0   | 1512 | 0.6965          | 0.3692 |
| 0.4159        | 9.0   | 1701 | 0.7172          | 0.3478 |
| 0.3924        | 10.0  | 1890 | 0.7182          | 0.3333 |


### Framework versions

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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "bert-base-german-cased", "model-index": [{"name": "Misinformation-Covid-bert-base-german-cased", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer base_model:bert-base-german-cased license:mit autotrain_compatible endpoints_compatible region:us