---
license: mit
base_model: bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Misinformation-Covidbert-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-Covidbert-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: 1.0461
- Accuracy: {'accuracy': 0.9116279069767442}
- F1: {'f1': 0.9518987341772153}

## 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         | F1                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------------:|
| 0.7824        | 1.0   | 216  | 0.5755          | {'accuracy': 0.8325581395348837} | {'f1': 0.9027027027027028} |
| 0.8006        | 2.0   | 432  | 1.0461          | {'accuracy': 0.9116279069767442} | {'f1': 0.9518987341772153} |


### Framework versions

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