DistilWav2Vec2 Adult/Child Speech Classifier 52M
DistilWav2Vec2 Adult/Child Speech Classifier is an audio classification model based on the wav2vec 2.0 architecture. This model is a distilled version of wav2vec2-adult-child-cls 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) |
---|---|---|---|
distil-wav2vec2-adult-child-cls-52m |
52M | 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 | 0.1301 | 96.03% | 0.9639 |
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate
: 3e-05train_batch_size
: 32eval_batch_size
: 32seed
: 42gradient_accumulation_steps
: 4total_train_batch_size
: 128optimizer
: Adam withbetas=(0.9,0.999)
andepsilon=1e-08
lr_scheduler_type
: linearlr_scheduler_warmup_ratio
: 0.1num_epochs
: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.212 | 1.0 | 96 | 0.1561 | 0.9561 | 0.9596 |
0.1523 | 2.0 | 192 | 0.1408 | 0.9575 | 0.9616 |
0.0844 | 3.0 | 288 | 0.1301 | 0.9603 | 0.9639 |
Disclaimer
Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
Authors
DistilWav2Vec2 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
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