---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-german-cased-finetuned-emotion-2-labels
  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. -->

# bert-base-german-cased-finetuned-emotion-2-labels

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: 0.9788
- Accuracy: 0.835
- F1: 0.8345

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6249        | 1.0   | 25   | 0.4990          | 0.775    | 0.7743 |
| 0.4072        | 2.0   | 50   | 0.4041          | 0.825    | 0.8250 |
| 0.2202        | 3.0   | 75   | 0.4166          | 0.84     | 0.8400 |
| 0.1028        | 4.0   | 100  | 0.4974          | 0.82     | 0.8191 |
| 0.0391        | 5.0   | 125  | 0.6061          | 0.79     | 0.7892 |
| 0.0175        | 6.0   | 150  | 0.6459          | 0.845    | 0.8449 |
| 0.0039        | 7.0   | 175  | 0.6933          | 0.84     | 0.8400 |
| 0.0033        | 8.0   | 200  | 0.7915          | 0.84     | 0.8396 |
| 0.001         | 9.0   | 225  | 0.9425          | 0.825    | 0.8250 |
| 0.0046        | 10.0  | 250  | 0.9074          | 0.82     | 0.82   |
| 0.001         | 11.0  | 275  | 0.9323          | 0.835    | 0.8348 |
| 0.0009        | 12.0  | 300  | 0.9144          | 0.84     | 0.8394 |
| 0.0003        | 13.0  | 325  | 0.9082          | 0.845    | 0.8450 |
| 0.0003        | 14.0  | 350  | 0.8913          | 0.84     | 0.8397 |
| 0.0003        | 15.0  | 375  | 0.9534          | 0.845    | 0.8450 |
| 0.0004        | 16.0  | 400  | 0.9498          | 0.835    | 0.8349 |
| 0.0027        | 17.0  | 425  | 0.9838          | 0.84     | 0.8400 |
| 0.0006        | 18.0  | 450  | 0.9853          | 0.845    | 0.8450 |
| 0.0003        | 19.0  | 475  | 0.9768          | 0.825    | 0.8243 |
| 0.0002        | 20.0  | 500  | 0.9788          | 0.835    | 0.8345 |


### Framework versions

- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 1.16.1
- Tokenizers 0.12.1
