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End of training

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  1. README.md +8 -7
README.md CHANGED
@@ -11,7 +11,7 @@ datasets:
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper Small fa - ArtificialCoincidence
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  results:
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  - task:
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  name: Automatic Speech Recognition
@@ -25,18 +25,18 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 61.15743759799093
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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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  should probably proofread and complete it, then remove this comment. -->
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- # Whisper Small fa - ArtificialCoincidence
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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: 0.6260
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- - Wer: 61.1574
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  ## Model description
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@@ -61,8 +61,8 @@ 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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- - lr_scheduler_warmup_steps: 500
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- - training_steps: 400
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -71,6 +71,7 @@ The following hyperparameters were used during training:
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|
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  | 0.9736 | 0.09 | 200 | 1.1516 | 69.9194 |
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  | 0.3892 | 0.17 | 400 | 0.6260 | 61.1574 |
 
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  ### Framework versions
 
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  metrics:
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  - wer
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  model-index:
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+ - name: Whisper Small fa
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  results:
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  - task:
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  name: Automatic Speech Recognition
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 59.0415273403355
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # Whisper Small fa
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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: 0.5556
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+ - Wer: 59.0415
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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: 600
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+ - training_steps: 600
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|
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  | 0.9736 | 0.09 | 200 | 1.1516 | 69.9194 |
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  | 0.3892 | 0.17 | 400 | 0.6260 | 61.1574 |
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+ | 0.3177 | 0.26 | 600 | 0.5556 | 59.0415 |
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  ### Framework versions