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README.md
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_7_0
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- generated_from_trainer
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datasets:
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model-index:
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- name:
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results:
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---
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should probably proofread and complete it, then remove this comment. -->
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# xls-r-uyghur-cv7
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UG dataset.
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It achieves the following results on the evaluation set:
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## Model description
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## Intended uses & limitations
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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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- automatic-speech-recognition
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- mozilla-foundation/common_voice_7_0
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- generated_from_trainer
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- ug
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- robust-speech-event
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datasets:
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- mozilla-foundation/common_voice_7_0
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model-index:
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- name: XLS-R-300M Uyghur CV7
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 7
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type: mozilla-foundation/common_voice_7_0
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args: ug
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metrics:
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- name: Test WER
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type: wer
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value: 25.845
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- name: Test CER
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type: cer
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value: 4.795
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---
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# XLS-R-300M Uyghur CV7
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - UG dataset.
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It achieves the following results on the evaluation set:
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## Model description
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For a description of the model architecture, see [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m)
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The model vocabulary consists of the alphabetic characters of the [Perso-Arabic script for the Uyghur language](https://omniglot.com/writing/uyghur.htm), with punctuation removed.
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## Intended uses & limitations
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This model is expected to be of some utility for low-fidelity use cases such as:
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- Draft video captions
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- Indexing of recorded broadcasts
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The model is not reliable enough to use as a substitute for live captions for accessibility purposes, and it should not be used in a manner that would infringe the privacy of any of the contributors to the Common Voice dataset nor any other speakers.
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## Training and evaluation data
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The combination of `train` and `dev` of common voice official splits were used as training data. The official `test` split was used as validation data as well as for final evaluation.
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## Training procedure
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The featurization layers of the XLS-R model are frozen while tuning a final CTC/LM layer on the Uyghur CV7 example sentences. A ramped learning rate is used with an initial warmup phase of 2000 steps, a max of 0.0001, and cooling back towards 0 for the remainder of the 18500 steps (100 epochs).
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### Training hyperparameters
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The following hyperparameters were used during training:
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