wav2vec2-audio-emotion-classification
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9518
- Accuracy: 0.7398
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.759 | 0.99 | 22 | 1.7087 | 0.3122 |
| 1.5568 | 1.98 | 44 | 1.4412 | 0.4923 |
| 1.2577 | 2.97 | 66 | 1.1467 | 0.7060 |
| 1.0768 | 4.0 | 89 | 1.0131 | 0.7215 |
| 0.9476 | 4.99 | 111 | 0.9633 | 0.7314 |
| 0.9094 | 5.93 | 132 | 0.9518 | 0.7398 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1