---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- emodb
metrics:
- accuracy
model-index:
- name: whisper-large-v3-de-emodb-emotion-classification
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Emo-DB
      type: emodb
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9439252336448598
---

<!-- 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-large-v3-de-emodb-emotion-classification

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Emo-DB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3724
- Accuracy: 0.9439

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3351        | 1.0   | 214  | 1.1022          | 0.4953   |
| 0.2644        | 2.0   | 428  | 0.7572          | 0.7477   |
| 0.3796        | 3.0   | 642  | 1.0055          | 0.8131   |
| 0.0038        | 4.0   | 856  | 1.0754          | 0.8131   |
| 0.001         | 5.0   | 1070 | 0.5485          | 0.9159   |
| 0.001         | 6.0   | 1284 | 0.5881          | 0.8785   |
| 0.0007        | 7.0   | 1498 | 0.3376          | 0.9439   |
| 0.0006        | 8.0   | 1712 | 0.3592          | 0.9439   |
| 0.0006        | 9.0   | 1926 | 0.3695          | 0.9439   |
| 0.0004        | 10.0  | 2140 | 0.3724          | 0.9439   |


### Framework versions

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