Wav2Vec2 XLS-R Adult/Child Speech Classifier is an audio classification model based on the XLS-R architecture. This model is a fine-tuned version of wav2vec2-xls-r-300m 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)|
||300M||XLS-R||Adult/Child Speech Classification Dataset|
The model achieves the following results on evaluation:
|Adult/Child Speech Classification||0.1851||94.69%||0.9508|
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.
Wav2Vec2 XLS-R Adult/Child Speech Classifier was trained and evaluated by Wilson Wongso. All computation and development are done on Kaggle.
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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