---
license: mit
base_model: bert-base-german-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Germeval24StageTask2
  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. -->

# Germeval24StageTask2

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: 0.5740
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 0.7979

## 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: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 175  | 0.6167          | 1.0       | 1.0    | 1.0 | 0.7589   |
| No log        | 2.0   | 350  | 0.5740          | 1.0       | 1.0    | 1.0 | 0.7979   |
| 0.5186        | 3.0   | 525  | 0.8370          | 1.0       | 1.0    | 1.0 | 0.7719   |
| 0.5186        | 4.0   | 700  | 0.7648          | 1.0       | 1.0    | 1.0 | 0.8153   |
| 0.5186        | 5.0   | 875  | 0.7703          | 1.0       | 1.0    | 1.0 | 0.7988   |
| 0.1581        | 6.0   | 1050 | 0.8545          | 1.0       | 1.0    | 1.0 | 0.8092   |
| 0.1581        | 7.0   | 1225 | 0.9456          | 1.0       | 1.0    | 1.0 | 0.8057   |
| 0.1581        | 8.0   | 1400 | 1.0018          | 1.0       | 1.0    | 1.0 | 0.8031   |
| 0.0573        | 9.0   | 1575 | 1.0635          | 1.0       | 1.0    | 1.0 | 0.8066   |
| 0.0573        | 10.0  | 1750 | 1.0481          | 1.0       | 1.0    | 1.0 | 0.8066   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1