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End of training

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  1. README.md +11 -11
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@@ -24,7 +24,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 40.43020749693614
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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
@@ -34,8 +34,8 @@ 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 15.0 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3828
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- - Wer: 40.4302
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|
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- | 0.6715 | 0.1129 | 500 | 0.7162 | 66.9030 |
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- | 0.4722 | 0.2258 | 1000 | 0.5434 | 54.6750 |
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- | 0.4207 | 0.3388 | 1500 | 0.4768 | 49.2076 |
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- | 0.3884 | 0.4517 | 2000 | 0.4404 | 45.1739 |
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- | 0.3734 | 0.5646 | 2500 | 0.4167 | 43.9420 |
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- | 0.3389 | 0.6775 | 3000 | 0.3994 | 41.2205 |
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- | 0.3405 | 0.7904 | 3500 | 0.3887 | 41.2110 |
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- | 0.3087 | 0.9033 | 4000 | 0.3828 | 40.4302 |
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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: 40.49254109791658
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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 15.0 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3827
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+ - Wer: 40.4925
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Wer |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|
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+ | 0.6714 | 0.1129 | 500 | 0.7163 | 66.8396 |
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+ | 0.4722 | 0.2258 | 1000 | 0.5435 | 54.3887 |
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+ | 0.4207 | 0.3388 | 1500 | 0.4766 | 49.0312 |
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+ | 0.3891 | 0.4517 | 2000 | 0.4403 | 45.2288 |
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+ | 0.3737 | 0.5646 | 2500 | 0.4167 | 44.0403 |
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+ | 0.3386 | 0.6775 | 3000 | 0.3994 | 41.2405 |
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+ | 0.3402 | 0.7904 | 3500 | 0.3887 | 41.2300 |
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+ | 0.3089 | 0.9033 | 4000 | 0.3827 | 40.4925 |
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  ### Framework versions