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update model card README.md

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@@ -20,8 +20,8 @@ should probably proofread and complete it, then remove this comment. -->
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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 - AB dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5885
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- - Wer: 0.5899
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  ## Model description
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@@ -48,7 +48,7 @@ The following hyperparameters were used during training:
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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: 750
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  - num_epochs: 100.0
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 7.5798 | 13.64 | 300 | 3.4349 | 1.0 |
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- | 3.1252 | 27.27 | 600 | 3.0706 | 1.0 |
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- | 2.2546 | 40.91 | 900 | 0.8427 | 0.7763 |
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- | 0.7564 | 54.55 | 1200 | 0.6129 | 0.6376 |
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- | 0.5239 | 68.18 | 1500 | 0.5769 | 0.6037 |
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- | 0.438 | 81.82 | 1800 | 0.5938 | 0.5915 |
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- | 0.3945 | 95.45 | 2100 | 0.5869 | 0.5861 |
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  ### Framework versions
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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 - AB dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5620
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+ - Wer: 0.5651
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  ## Model description
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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: 100.0
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 9.6445 | 13.64 | 300 | 4.3963 | 1.0 |
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+ | 3.6459 | 27.27 | 600 | 3.2267 | 1.0 |
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+ | 3.0978 | 40.91 | 900 | 3.0927 | 1.0 |
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+ | 2.8357 | 54.55 | 1200 | 2.1462 | 1.0029 |
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+ | 1.2723 | 68.18 | 1500 | 0.6747 | 0.6996 |
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+ | 0.6528 | 81.82 | 1800 | 0.5928 | 0.6422 |
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+ | 0.4905 | 95.45 | 2100 | 0.5587 | 0.5681 |
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  ### Framework versions