metadata
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
whisper-large-v3-de-emodb-emotion-classification
This model is a fine-tuned version of 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