---
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: 0.4272
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 0.8575

## 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   | 150  | 0.4852          | 1.0       | 1.0    | 1.0 | 0.8099   |
| No log        | 2.0   | 300  | 0.4305          | 1.0       | 1.0    | 1.0 | 0.8499   |
| No log        | 3.0   | 450  | 0.4272          | 1.0       | 1.0    | 1.0 | 0.8575   |
| 0.4985        | 4.0   | 600  | 0.4776          | 1.0       | 1.0    | 1.0 | 0.8510   |
| 0.4985        | 5.0   | 750  | 0.5090          | 1.0       | 1.0    | 1.0 | 0.8629   |
| 0.4985        | 6.0   | 900  | 0.5940          | 1.0       | 1.0    | 1.0 | 0.8521   |
| 0.1257        | 7.0   | 1050 | 0.5592          | 1.0       | 1.0    | 1.0 | 0.8618   |
| 0.1257        | 8.0   | 1200 | 0.6132          | 1.0       | 1.0    | 1.0 | 0.8521   |
| 0.1257        | 9.0   | 1350 | 0.6580          | 1.0       | 1.0    | 1.0 | 0.8639   |
| 0.0448        | 10.0  | 1500 | 0.6727          | 1.0       | 1.0    | 1.0 | 0.8629   |


### Framework versions

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