---
license: mit
base_model: dbmdz/bert-base-german-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: class_classificator_results
  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. -->

# class_classificator_results

This model is a fine-tuned version of [dbmdz/bert-base-german-uncased](https://huggingface.co./dbmdz/bert-base-german-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7400
- Precision: 0.9096
- Recall: 0.9096
- F1: 0.9096
- Accuracy: 0.9096

## 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: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.321         | 1.0   | 2527  | 1.1812          | 0.8505    | 0.8505 | 0.8505 | 0.8505   |
| 0.8803        | 2.0   | 5054  | 0.8872          | 0.8850    | 0.8850 | 0.8850 | 0.8850   |
| 0.6046        | 3.0   | 7581  | 0.7477          | 0.9042    | 0.9042 | 0.9042 | 0.9042   |
| 0.4113        | 4.0   | 10108 | 0.7400          | 0.9096    | 0.9096 | 0.9096 | 0.9096   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1