LABEL_0 LABEL_1 LABEL_10 LABEL_11 LABEL_12 LABEL_13 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-14-labels
  results: []
---

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# bert-base-german-cased-finetuned-emotion-14-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: 1.1072
- Accuracy: 0.7304
- F1: 0.7302

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.9084        | 1.0   | 128  | 1.3889          | 0.5735   | 0.5631 |
| 1.0961        | 2.0   | 256  | 1.0875          | 0.6422   | 0.6379 |
| 0.7211        | 3.0   | 384  | 0.9900          | 0.6873   | 0.6859 |
| 0.4556        | 4.0   | 512  | 0.9495          | 0.7137   | 0.7166 |
| 0.2916        | 5.0   | 640  | 0.9807          | 0.7069   | 0.7054 |
| 0.1784        | 6.0   | 768  | 0.9956          | 0.7196   | 0.7199 |
| 0.1134        | 7.0   | 896  | 1.0471          | 0.7167   | 0.7169 |
| 0.0759        | 8.0   | 1024 | 1.0822          | 0.7235   | 0.7225 |
| 0.0502        | 9.0   | 1152 | 1.1048          | 0.7157   | 0.7173 |
| 0.041         | 10.0  | 1280 | 1.1072          | 0.7304   | 0.7302 |


### Framework versions

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