---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: german_tc_professions_debates
  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. -->

# german_tc_professions_debates

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: 0.0487
- Precision: 0.9439
- Recall: 0.9739
- F1: 0.9587
- Accuracy: 0.9907

## 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: 5e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 31   | 0.0423          | 0.9383    | 0.9646 | 0.9512 | 0.9894   |
| No log        | 2.0   | 62   | 0.0513          | 0.9017    | 0.9757 | 0.9373 | 0.9883   |
| No log        | 3.0   | 93   | 0.0444          | 0.9355    | 0.9739 | 0.9543 | 0.9902   |
| No log        | 4.0   | 124  | 0.0474          | 0.9457    | 0.9739 | 0.9596 | 0.9909   |
| No log        | 5.0   | 155  | 0.0487          | 0.9439    | 0.9739 | 0.9587 | 0.9907   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3