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End of training

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README.md CHANGED
@@ -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: 59.907017932255926
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.7722
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- - Wer: 59.9070
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  ## Model description
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@@ -53,7 +53,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0005
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
@@ -67,10 +67,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|
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- | 1.7046 | 2.2222 | 1000 | 3.0091 | 85.5952 |
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- | 0.5748 | 4.4444 | 2000 | 2.7369 | 74.2750 |
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- | 0.1547 | 6.6667 | 3000 | 2.8273 | 66.2534 |
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- | 0.0288 | 8.8889 | 4000 | 2.7722 | 59.9070 |
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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: 15.897728895872017
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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-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6303
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+ - Wer: 15.8977
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.1189 | 2.2222 | 1000 | 0.4313 | 15.6049 |
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+ | 0.0179 | 4.4444 | 2000 | 0.5332 | 16.1263 |
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+ | 0.0039 | 6.6667 | 3000 | 0.5926 | 15.8049 |
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+ | 0.0012 | 8.8889 | 4000 | 0.6303 | 15.8977 |
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  ### Framework versions
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