wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-babycry-v2
This model is a fine-tuned version of ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8522
- Accuracy: {'accuracy': 0.8043478260869565}
- F1: 0.7171
- Precision: 0.6470
- Recall: 0.8043
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6078 | 0.4854 | 25 | 0.8682 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
| 0.7269 | 0.9709 | 50 | 0.8559 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
| 0.6815 | 1.4563 | 75 | 0.8204 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
| 0.6144 | 1.9417 | 100 | 0.8417 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
| 0.6246 | 2.4272 | 125 | 0.8454 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
| 0.5687 | 2.9126 | 150 | 0.8527 | {'accuracy': 0.8043478260869565} | 0.7171 | 0.6470 | 0.8043 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1