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End of training

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README.md CHANGED
@@ -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: 23.544963481436394
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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 librispeech_asr dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5354
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- - Wer: 23.5450
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  ## Model description
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@@ -68,16 +68,16 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|
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- | 1.0518 | 0.12 | 1000 | 0.7491 | 31.7103 |
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- | 0.8884 | 0.24 | 2000 | 0.6588 | 27.4003 |
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- | 0.8061 | 0.36 | 3000 | 0.6177 | 26.4569 |
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- | 0.8549 | 0.48 | 4000 | 0.5888 | 25.5002 |
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- | 0.7836 | 0.6 | 5000 | 0.5688 | 25.8939 |
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- | 0.691 | 0.72 | 6000 | 0.5542 | 24.1574 |
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- | 0.7044 | 0.84 | 7000 | 0.5429 | 23.5450 |
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- | 0.7309 | 0.97 | 8000 | 0.5354 | 23.5450 |
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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: 2.8092665855143033
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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 librispeech_asr dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0813
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+ - Wer: 2.8093
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.0956 | 0.12 | 1000 | 0.1065 | 3.6519 |
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+ | 0.1002 | 0.24 | 2000 | 0.0997 | 3.5453 |
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+ | 0.0841 | 0.36 | 3000 | 0.0941 | 3.3057 |
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+ | 0.0839 | 0.48 | 4000 | 0.0905 | 3.1783 |
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+ | 0.0821 | 0.6 | 5000 | 0.0855 | 2.9595 |
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+ | 0.0626 | 0.72 | 6000 | 0.0839 | 2.9310 |
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+ | 0.0643 | 0.84 | 7000 | 0.0821 | 2.8112 |
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+ | 0.0908 | 0.97 | 8000 | 0.0813 | 2.8093 |
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  ### Framework versions
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