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README.md
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# afrospeech-wav2vec-yor
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [crowd-speech-africa](https://huggingface.co/datasets/chrisjay/crowd-speech-africa), which was a crowd-sourced dataset collected using the [afro-speech Space](https://huggingface.co/spaces/chrisjay/afro-speech).
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- F1: 0.83
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- Accuracy: 0.83
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The confusion matrix below helps to give a better look at the model's performance across the digits. Through it, we can see the precision and recall of the model as well as other important insights.
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![confusion matrix](afrospeech-wav2vec-yor_confusion_matrix_VALID.png)
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## Training and evaluation data
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![digits-bar-plot-for-afrospeech](digits-bar-plot-for-afrospeech-wav2vec-yor.png)
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### Training hyperparameters
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# afrospeech-wav2vec-yor
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [crowd-speech-africa](https://huggingface.co/datasets/chrisjay/crowd-speech-africa), which was a crowd-sourced dataset collected using the [afro-speech Space](https://huggingface.co/spaces/chrisjay/afro-speech).
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## Training and evaluation data
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![digits-bar-plot-for-afrospeech](digits-bar-plot-for-afrospeech-wav2vec-yor.png)
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## Evaluation performace
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It achieves the following results on the [validation set](VALID_yoruba_yor_audio_data.csv):
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- F1: 0.83
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- Accuracy: 0.83
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The confusion matrix below helps to give a better look at the model's performance across the digits. Through it, we can see the precision and recall of the model as well as other important insights.
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![confusion matrix](afrospeech-wav2vec-yor_confusion_matrix_VALID.png)
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### Training hyperparameters
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