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End of training

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  1. README.md +13 -13
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@@ -20,7 +20,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 64.63375512386384
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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
@@ -30,8 +30,8 @@ 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 6.1 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6644
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- - Wer: 64.6338
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  ## Model description
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@@ -64,16 +64,16 @@ 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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- | 2.0563 | 6.6667 | 100 | 2.2740 | 83.8603 |
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- | 0.9188 | 13.3333 | 200 | 1.7748 | 76.3393 |
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- | 0.4133 | 20.0 | 300 | 1.6575 | 69.3138 |
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- | 0.1672 | 26.6667 | 400 | 1.6334 | 67.2750 |
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- | 0.0603 | 33.3333 | 500 | 1.6320 | 66.4160 |
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- | 0.0245 | 40.0 | 600 | 1.6434 | 65.3573 |
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- | 0.0138 | 46.6667 | 700 | 1.6523 | 64.7229 |
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- | 0.0104 | 53.3333 | 800 | 1.6592 | 64.0634 |
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- | 0.0089 | 60.0 | 900 | 1.6633 | 64.6551 |
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- | 0.0083 | 66.6667 | 1000 | 1.6644 | 64.6338 |
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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: 64.62662626982713
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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 6.1 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6643
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+ - Wer: 64.6266
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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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+ | 2.0562 | 6.6667 | 100 | 2.2740 | 83.4860 |
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+ | 0.9187 | 13.3333 | 200 | 1.7749 | 76.7385 |
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+ | 0.4133 | 20.0 | 300 | 1.6576 | 69.3317 |
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+ | 0.1671 | 26.6667 | 400 | 1.6334 | 67.2679 |
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+ | 0.0603 | 33.3333 | 500 | 1.6319 | 66.2770 |
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+ | 0.0245 | 40.0 | 600 | 1.6433 | 65.6496 |
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+ | 0.0138 | 46.6667 | 700 | 1.6522 | 64.6730 |
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+ | 0.0104 | 53.3333 | 800 | 1.6591 | 64.5019 |
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+ | 0.0089 | 60.0 | 900 | 1.6632 | 64.4876 |
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+ | 0.0083 | 66.6667 | 1000 | 1.6643 | 64.6266 |
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  ### Framework versions