wav2vec2-emotion-recognition
This model is a fine-tuned version of ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2221
- Accuracy: 0.9479
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 144 | 0.7688 | 0.8507 |
| No log | 2.0 | 288 | 0.4408 | 0.8993 |
| No log | 3.0 | 432 | 0.2798 | 0.9375 |
| 0.7338 | 4.0 | 576 | 0.2184 | 0.9479 |
| 0.7338 | 5.0 | 720 | 0.2221 | 0.9479 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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