---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- emodb
metrics:
- accuracy
language:
- de
model-index:
- name: whisper-tiny-de-emodb-emotion-classification
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Emo-DB
      type: emodb
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9158878504672897
---

<!-- 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. -->

# whisper-tiny-de-emodb-emotion-classification

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the german Emo-DB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4912
- Accuracy: 0.9159

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3193        | 1.0   | 214  | 1.4616          | 0.3925   |
| 0.1342        | 2.0   | 428  | 1.0384          | 0.6449   |
| 0.0582        | 3.0   | 642  | 1.5578          | 0.6542   |
| 0.6567        | 4.0   | 856  | 1.2043          | 0.7850   |
| 0.0202        | 5.0   | 1070 | 0.5967          | 0.8598   |
| 0.0008        | 6.0   | 1284 | 0.6261          | 0.8692   |
| 0.0006        | 7.0   | 1498 | 0.5857          | 0.8785   |
| 0.0004        | 8.0   | 1712 | 0.4992          | 0.9065   |
| 0.0004        | 9.0   | 1926 | 0.4943          | 0.9159   |
| 0.0003        | 10.0  | 2140 | 0.4912          | 0.9159   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1