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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_17_0 - UG dataset. It achieves the following results on the evaluation set:

Loss: 1.2888
Model description
For a description of the model architecture, see facebook/wav2vec2-xls-r-300m

The model vocabulary consists of the alphabetic characters of the Perso-Arabic script for the Uyghur language, with punctuation removed.

Intended uses & limitations
This model is expected to be of some utility for low-fidelity use cases such as:

Draft video captions
Indexing of recorded broadcasts
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.
Training and evaluation data
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.

Training procedure
The featurization layers of the XLS-R model are frozen while tuning a final CTC/LM layer on the Uyghur CV17 example sentences.

Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0001
train_batch_size: 16
eval_batch_size: 16
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_train_epochs=3,

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- ---
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- license: apache-2.0
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- language:
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- - ug
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- base_model:
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- - facebook/wav2vec2-xls-r-300m
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- library_name: adapter-transformers
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- datasets:
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- - mozilla-foundation/common_voice_17_0
 
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  ---
 
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+ ---
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+ license: apache-2.0
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+ language:
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+ - ug
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+ base_model:
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+ - facebook/wav2vec2-xls-r-300m
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+ library_name: adapter-transformers
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+ datasets:
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+ - mozilla-foundation/common_voice_17_0
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+ pipeline_tag: text-to-speech
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  ---