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README.md
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---
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language:
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- ug
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_8_0
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- generated_from_trainer
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datasets:
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- common_voice
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model-index:
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- name: xls-r-uyghur-cv8
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# xls-r-uyghur-cv8
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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_8_0 - UG dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2430
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- Wer: 0.3804
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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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: 7.5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 2000
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- num_epochs: 50.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 3.6871 | 2.66 | 500 | 3.5374 | 1.0 |
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| 3.1501 | 5.32 | 1000 | 3.1278 | 1.0 |
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| 1.5843 | 7.97 | 1500 | 0.6358 | 0.6914 |
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| 1.3378 | 10.64 | 2000 | 0.4422 | 0.5925 |
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| 1.2595 | 13.3 | 2500 | 0.3921 | 0.5512 |
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| 1.1643 | 15.95 | 3000 | 0.3507 | 0.5149 |
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| 1.1352 | 18.61 | 3500 | 0.3351 | 0.5019 |
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| 1.1113 | 21.28 | 4000 | 0.3153 | 0.4845 |
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| 1.0914 | 23.93 | 4500 | 0.3050 | 0.4594 |
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| 1.0468 | 26.59 | 5000 | 0.2890 | 0.4470 |
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| 1.0473 | 29.25 | 5500 | 0.2755 | 0.4331 |
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| 1.0065 | 31.91 | 6000 | 0.2718 | 0.4264 |
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| 0.9794 | 34.57 | 6500 | 0.2646 | 0.4193 |
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| 0.9849 | 37.23 | 7000 | 0.2610 | 0.4058 |
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| 0.9496 | 39.89 | 7500 | 0.2522 | 0.3985 |
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| 0.9367 | 42.55 | 8000 | 0.2514 | 0.3947 |
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| 0.9295 | 45.21 | 8500 | 0.2458 | 0.3883 |
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| 0.9187 | 47.87 | 9000 | 0.2439 | 0.3833 |
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### Framework versions
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- Transformers 4.16.0.dev0
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- Pytorch 1.10.1+cu102
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- Datasets 1.18.2.dev0
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- Tokenizers 0.11.0
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