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update model card README.md

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@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 0.19205164413960057
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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
@@ -33,9 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FLEURS dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3106
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- - Wer Ortho: 0.2256
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- - Wer: 0.1921
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  ## Model description
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@@ -63,7 +63,7 @@ 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: constant_with_warmup
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  - lr_scheduler_warmup_steps: 50
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- - num_epochs: 12
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  ### Training results
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@@ -75,12 +75,7 @@ The following hyperparameters were used during training:
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  | 0.0454 | 4.0 | 1099 | 0.2667 | 0.2315 | 0.1985 |
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  | 0.028 | 5.0 | 1374 | 0.2579 | 0.2151 | 0.1822 |
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  | 0.022 | 6.0 | 1649 | 0.2674 | 0.2188 | 0.1863 |
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- | 0.0202 | 7.0 | 1924 | 0.2719 | 0.2140 | 0.1790 |
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- | 0.0129 | 8.0 | 2199 | 0.2894 | 0.2219 | 0.1834 |
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- | 0.0218 | 9.0 | 2473 | 0.2861 | 0.2180 | 0.1831 |
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- | 0.0144 | 10.0 | 2748 | 0.3076 | 0.2211 | 0.1874 |
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- | 0.0157 | 11.0 | 3023 | 0.3094 | 0.2264 | 0.1900 |
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- | 0.0114 | 11.96 | 3288 | 0.3106 | 0.2256 | 0.1921 |
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.17739223993006523
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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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  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the FLEURS dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2734
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+ - Wer Ortho: 0.2102
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+ - Wer: 0.1774
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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: constant_with_warmup
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  - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 7
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  ### Training results
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  | 0.0454 | 4.0 | 1099 | 0.2667 | 0.2315 | 0.1985 |
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  | 0.028 | 5.0 | 1374 | 0.2579 | 0.2151 | 0.1822 |
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  | 0.022 | 6.0 | 1649 | 0.2674 | 0.2188 | 0.1863 |
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+ | 0.0202 | 6.98 | 1918 | 0.2734 | 0.2102 | 0.1774 |
 
 
 
 
 
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  ### Framework versions