LABEL_0 LABEL_1 LABEL_10 LABEL_11 LABEL_12 LABEL_13 LABEL_14 LABEL_15 LABEL_16 LABEL_2 LABEL_3 LABEL_4 LABEL_5 LABEL_6 LABEL_7 LABEL_8 LABEL_9
---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-german-cased-finetuned-emotion-17-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-17-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: 1.4977
- Accuracy: 0.6163
- F1: 0.6177

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.1684        | 1.0   | 177  | 1.6777          | 0.4693   | 0.4512 |
| 1.4461        | 2.0   | 354  | 1.4281          | 0.5470   | 0.5374 |
| 1.0495        | 3.0   | 531  | 1.2895          | 0.5986   | 0.5968 |
| 0.7524        | 4.0   | 708  | 1.2638          | 0.6134   | 0.6127 |
| 0.5295        | 5.0   | 885  | 1.3287          | 0.6127   | 0.6103 |
| 0.367         | 6.0   | 1062 | 1.3906          | 0.6021   | 0.5994 |
| 0.256         | 7.0   | 1239 | 1.4109          | 0.6127   | 0.6128 |
| 0.1805        | 8.0   | 1416 | 1.4692          | 0.6113   | 0.6147 |
| 0.1429        | 9.0   | 1593 | 1.4945          | 0.6113   | 0.6131 |
| 0.1147        | 10.0  | 1770 | 1.4977          | 0.6163   | 0.6177 |


### Framework versions

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