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End of training

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  1. README.md +15 -12
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@@ -25,7 +25,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 43.03652465083491
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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
@@ -35,8 +35,8 @@ 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: 0.2531
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- - Wer: 43.0365
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  ## Model description
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@@ -61,21 +61,24 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - training_steps: 4000
 
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  - mixed_precision_training: Native AMP
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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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- | 0.1467 | 1.06 | 500 | 0.1944 | 52.8704 |
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- | 0.0769 | 2.12 | 1000 | 0.1651 | 47.0106 |
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- | 0.044 | 3.18 | 1500 | 0.1693 | 45.1381 |
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- | 0.0203 | 4.24 | 2000 | 0.1860 | 43.4903 |
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- | 0.0097 | 5.3 | 2500 | 0.2096 | 43.9618 |
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- | 0.0039 | 6.36 | 3000 | 0.2311 | 43.2877 |
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- | 0.0019 | 7.42 | 3500 | 0.2454 | 43.2612 |
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- | 0.0009 | 8.47 | 4000 | 0.2531 | 43.0365 |
 
 
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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: 42.212627219456316
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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: 0.2751
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+ - Wer: 42.2126
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 200
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+ - training_steps: 5000
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  - mixed_precision_training: Native AMP
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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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+ | 0.163 | 1.06 | 500 | 0.2064 | 55.6065 |
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+ | 0.0862 | 2.12 | 1000 | 0.1675 | 47.1869 |
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+ | 0.0475 | 3.18 | 1500 | 0.1696 | 44.8561 |
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+ | 0.0239 | 4.24 | 2000 | 0.1848 | 43.2436 |
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+ | 0.0119 | 5.3 | 2500 | 0.2081 | 43.5608 |
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+ | 0.0058 | 6.36 | 3000 | 0.2262 | 43.0718 |
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+ | 0.0024 | 7.42 | 3500 | 0.2427 | 42.4726 |
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+ | 0.0009 | 8.47 | 4000 | 0.2611 | 42.6356 |
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+ | 0.0005 | 9.53 | 4500 | 0.2709 | 42.3492 |
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+ | 0.0004 | 10.59 | 5000 | 0.2751 | 42.2126 |
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  ### Framework versions