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||#params||Arch.||Training/Validation data (text)|
||52M||wav2vec 2.0||Adult/Child Speech Classification Dataset|
The model achieves the following results on evaluation:
|Adult/Child Speech Classification||0.1301||96.03%||0.9639|
The following hyperparameters were used during training:
optimizer: Adam with
|Training Loss||Epoch||Step||Validation Loss||Accuracy||F1|
Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
DistilWav2Vec2 Adult/Child Speech Classifier was trained and evaluated by Wilson Wongso. All computation and development are done on Kaggle.
- Transformers 4.16.2
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
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