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update model card README.md

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@@ -1,39 +1,38 @@
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  ---
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  license: apache-2.0
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  tags:
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- - whisper-event
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  - generated_from_trainer
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  datasets:
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- - google/fleurs
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper Tiny Pashto
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  results:
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  - task:
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  name: Automatic Speech Recognition
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  type: automatic-speech-recognition
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  dataset:
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- name: google/fleurs ps_af
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- type: google/fleurs
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  config: ps_af
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  split: test
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  args: ps_af
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  metrics:
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  - name: Wer
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  type: wer
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- value: 60.05599273607748
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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 Tiny Pashto
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- This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs ps_af dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8710
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- - Wer: 60.0560
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  ## Model description
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@@ -59,7 +58,7 @@ 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: 30
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- - training_steps: 500
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -71,6 +70,11 @@ The following hyperparameters were used during training:
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  | 0.5474 | 7.5 | 300 | 0.8744 | 60.5554 |
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  | 0.4646 | 10.0 | 400 | 0.8710 | 60.0560 |
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  | 0.4557 | 12.5 | 500 | 0.8732 | 59.4658 |
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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  tags:
 
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  - generated_from_trainer
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  datasets:
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+ - fleurs
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  metrics:
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  - wer
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  model-index:
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+ - name: openai/whisper-base
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  results:
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  - task:
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  name: Automatic Speech Recognition
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  type: automatic-speech-recognition
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  dataset:
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+ name: fleurs
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+ type: fleurs
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  config: ps_af
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  split: test
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  args: ps_af
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 59.200968523002416
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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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+ # openai/whisper-base
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+ This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the fleurs dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9339
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+ - Wer: 59.2010
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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: 30
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+ - training_steps: 1000
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  | 0.5474 | 7.5 | 300 | 0.8744 | 60.5554 |
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  | 0.4646 | 10.0 | 400 | 0.8710 | 60.0560 |
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  | 0.4557 | 12.5 | 500 | 0.8732 | 59.4658 |
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+ | 0.3882 | 15.0 | 600 | 0.8819 | 59.0648 |
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+ | 0.3346 | 17.5 | 700 | 0.9032 | 59.4809 |
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+ | 0.2947 | 20.0 | 800 | 0.9144 | 59.7685 |
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+ | 0.2724 | 22.5 | 900 | 0.9289 | 58.9815 |
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+ | 0.2785 | 25.0 | 1000 | 0.9339 | 59.2010 |
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  ### Framework versions