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README.md
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# ctrlv-speechrecognition-model
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.4730
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- Wer: 0.3031
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## Model description
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More information needed
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 1.18.3
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- Tokenizers 0.10.3
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# ctrlv-speechrecognition-model
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the TIMIT dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4730
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- Wer: 0.3031
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## Test WER in TIMIT dataset
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- Wer: 0.189
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## Model description
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More information needed
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 1.18.3
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- Tokenizers 0.10.3
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