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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 Small 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: 56.651029055690074
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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 Pashto
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- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 1.2281
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- - Wer: 56.6510
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  ## Model description
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@@ -52,29 +51,28 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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- - train_batch_size: 32
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- - eval_batch_size: 16
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  - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 64
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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: 700
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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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- | 2.1183 | 3.7 | 100 | 1.3170 | 76.9522 |
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- | 0.8565 | 7.41 | 200 | 0.9367 | 61.9930 |
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- | 0.2246 | 11.11 | 300 | 0.9642 | 58.8302 |
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- | 0.054 | 14.81 | 400 | 1.0876 | 57.9903 |
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- | 0.0159 | 18.52 | 500 | 1.1798 | 57.8768 |
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- | 0.0045 | 22.22 | 600 | 1.2309 | 56.6510 |
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- | 0.0026 | 100.0 | 700 | 1.2581 | 56.8478 |
 
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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-small
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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: 56.75696125907991
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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-small
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fleurs dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2710
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+ - Wer: 56.7570
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-07
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+ - train_batch_size: 64
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+ - eval_batch_size: 32
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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: 800
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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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+ | 2.1183 | 3.7 | 100 | 1.3170 | 76.9522 |
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+ | 0.8565 | 7.41 | 200 | 0.9367 | 61.9930 |
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+ | 0.2246 | 11.11 | 300 | 0.9642 | 58.8302 |
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+ | 0.054 | 14.81 | 400 | 1.0876 | 57.9903 |
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+ | 0.0159 | 18.52 | 500 | 1.1798 | 57.8768 |
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+ | 0.0045 | 22.22 | 600 | 1.2309 | 56.6510 |
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+ | 0.0026 | 100.0 | 700 | 1.2581 | 56.8478 |
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+ | 0.0023 | 114.29 | 800 | 1.2710 | 56.7570 |
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  ### Framework versions