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# Misinformation-Covid-Articles

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: 0.1395
- Accuracy: 0.9840

## 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-05
- 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1266        | 1.0   | 3609  | 0.1224          | 0.9703   |
| 0.0639        | 2.0   | 7218  | 0.1170          | 0.9735   |
| 0.0437        | 3.0   | 10827 | 0.1230          | 0.9808   |
| 0.0148        | 4.0   | 14436 | 0.1209          | 0.9832   |
| 0.0044        | 5.0   | 18045 | 0.1395          | 0.9840   |


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