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  # wav2vec2-conformer-rel-pos-large-finetuned-speech-commands
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- This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the speech_commands dataset.
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- It has been trained for 10 epochs on the [speech_commands](https://huggingface.co/datasets/speech_commands) dataset:
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- - subset v0.02
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- - full training set
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- - full validation set
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5245
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  - Accuracy: 0.9724
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- ## Model description
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- ## Intended uses & limitations
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  The model can spot one of the following keywords: "Yes", "No", "Up", "Down", "Left", "Right", "On", "Off", "Stop", "Go", "Zero", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine", "Bed", "Bird", "Cat", "Dog", "Happy", "House", "Marvin", "Sheila", "Tree", "Wow", "Backward", "Forward", "Follow", "Learn", "Visual".
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- ## Training and evaluation data
 
 
 
 
 
 
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- ## Training procedure
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- ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
 
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  # wav2vec2-conformer-rel-pos-large-finetuned-speech-commands
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+ This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the [speech_commands](https://huggingface.co/datasets/speech_commands) dataset.
 
 
 
 
 
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5245
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  - Accuracy: 0.9724
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+ ### Model description
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+ TBD
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+ #### Intended uses & limitations
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  The model can spot one of the following keywords: "Yes", "No", "Up", "Down", "Left", "Right", "On", "Off", "Stop", "Go", "Zero", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine", "Bed", "Bird", "Cat", "Dog", "Happy", "House", "Marvin", "Sheila", "Tree", "Wow", "Backward", "Forward", "Follow", "Learn", "Visual".
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+ ### Training and evaluation data
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+
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+ - subset v0.02
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+ - full training set
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+ - full validation set
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+
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+ ### Training procedure
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+ TBD
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+ ###Training hyperparameters
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05