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Merge branch 'main' of https://huggingface.co/patrickvonplaten/wav2vec2-large-xls-r-300m-common_voice-tr-ft into main

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  1. README.md +9 -7
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@@ -20,9 +20,9 @@ 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 COMMON_VOICE - TR dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3823
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- - Wer: 0.3209
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- - Cer: 0.0771
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  ## Model description
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@@ -52,7 +52,7 @@ The following hyperparameters were used during training:
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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: 500
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- - num_epochs: 75.0
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -64,9 +64,11 @@ The following hyperparameters were used during training:
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  | 0.4343 | 27.27 | 1500 | 0.3819 | 0.4060 | 0.1012 |
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  | 0.4401 | 36.36 | 2000 | 0.3991 | 0.3954 | 0.1001 |
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  | 0.2647 | 45.45 | 2500 | 0.3901 | 0.3689 | 0.0914 |
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- | 0.2656 | 54.55 | 3000 | 0.3866 | 0.3463 | 0.0852 |
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- | 0.2586 | 63.64 | 3500 | 0.3779 | 0.3297 | 0.0804 |
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- | 0.2041 | 72.73 | 4000 | 0.3854 | 0.3234 | 0.0776 |
 
 
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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 COMMON_VOICE - TR dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4179
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+ - Wer: 0.3071
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+ - Cer: 0.0736
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  ## Model description
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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: 500
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+ - num_epochs: 100.0
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 0.4343 | 27.27 | 1500 | 0.3819 | 0.4060 | 0.1012 |
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  | 0.4401 | 36.36 | 2000 | 0.3991 | 0.3954 | 0.1001 |
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  | 0.2647 | 45.45 | 2500 | 0.3901 | 0.3689 | 0.0914 |
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+ | 0.2656 | 54.55 | 3000 | 0.4284 | 0.3463 | 0.0852 |
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+ | 0.2586 | 63.64 | 3500 | 0.4084 | 0.3297 | 0.0804 |
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+ | 0.2041 | 72.73 | 4000 | 0.3907 | 0.3193 | 0.0781 |
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+ | 0.4265 | 81.82 | 4500 | 0.4265 | 0.3120 | 0.0755 |
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+ | 0.2041 | 90.91 | 5000 | 0.4240 | 0.3071 | 0.0736 |
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  ### Framework versions