Wav2Vec2 Adult/Child Speech Classifier
Wav2Vec2 Adult/Child Speech Classifier is an audio classification model based on the wav2vec 2.0 architecture. This model is a fine-tuned version of wav2vec2-base on a private adult/child speech classification dataset.
This model was trained using HuggingFace's PyTorch framework. All training was done on a Tesla P100, provided by Kaggle. Training metrics were logged via Tensorboard.
Model
| Model | #params | Arch. | Training/Validation data (text) |
|---|---|---|---|
wav2vec2-adult-child-cls | 91M | wav2vec 2.0 | Adult/Child Speech Classification Dataset |
Evaluation Results
The model achieves the following results on evaluation:
| Dataset | Loss | Accuracy | F1 |
|---|---|---|---|
| Adult/Child Speech Classification | 0.1682 | 95.80% | 0.9618 |
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 3e-05train_batch_size: 32eval_batch_size: 32seed: 42optimizer: Adam withbetas=(0.9,0.999)andepsilon=1e-08lr_scheduler_type: linearlr_scheduler_warmup_ratio: 0.1num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2709 | 1.0 | 384 | 0.2616 | 0.9104 | 0.9142 |
| 0.2112 | 2.0 | 768 | 0.1826 | 0.9386 | 0.9421 |
| 0.1755 | 3.0 | 1152 | 0.1898 | 0.9354 | 0.9428 |
| 0.0915 | 4.0 | 1536 | 0.1682 | 0.9580 | 0.9618 |
| 0.1042 | 5.0 | 1920 | 0.1717 | 0.9511 | 0.9554 |
Disclaimer
Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
Authors
Wav2Vec2 Adult/Child Speech Classifier was trained and evaluated by Wilson Wongso. All computation and development are done on Kaggle.
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3