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End of training

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  1. README.md +13 -13
  2. generation_config.json +10 -26
README.md CHANGED
@@ -2,7 +2,7 @@
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  language:
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  - nl
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  license: apache-2.0
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- base_model: openai/whisper-small
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  tags:
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  - nl-asr-leaderboard
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  - generated_from_trainer
@@ -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 NL - Noise
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  results:
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  - task:
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  name: Automatic Speech Recognition
@@ -20,23 +20,23 @@ model-index:
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  name: Common Voice 11.0
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  type: mozilla-foundation/common_voice_11_0
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  config: nl
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- split: None
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  args: 'config: nl, split: test'
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  metrics:
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  - name: Wer
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  type: wer
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- value: 32.565492321589886
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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 NL - Noise
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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: 0.5674
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- - Wer: 32.5655
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  ## Model description
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@@ -62,15 +62,15 @@ The following hyperparameters were used during training:
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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: 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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- | 0.3571 | 0.39 | 2000 | 0.6279 | 35.4562 |
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- | 0.2991 | 0.78 | 4000 | 0.5674 | 32.5655 |
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  ### Framework versions
 
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  language:
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  - nl
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  license: apache-2.0
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+ base_model: openai/whisper-medium
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  tags:
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  - nl-asr-leaderboard
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  - generated_from_trainer
 
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  metrics:
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  - wer
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  model-index:
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+ - name: Whisper Medium NL - Noise
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  results:
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  - task:
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  name: Automatic Speech Recognition
 
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  name: Common Voice 11.0
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  type: mozilla-foundation/common_voice_11_0
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  config: nl
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+ split: test[:250]
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  args: 'config: nl, split: test'
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 22.04155374887082
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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 Medium NL - Noise
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) 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: 0.3982
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+ - Wer: 22.0416
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  ## Model description
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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: 10000
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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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+ | 0.1974 | 0.97 | 5000 | 0.4473 | 25.7904 |
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+ | 0.0668 | 1.95 | 10000 | 0.3982 | 22.0416 |
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  ### Framework versions
generation_config.json CHANGED
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