ihanif commited on
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update model card README.md

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- .run_speech_recognition_seq2seq_streaming.py.swp filter=lfs diff=lfs merge=lfs -text
 
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.run_speech_recognition_seq2seq_streaming.py.swp DELETED
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- oid sha256:5afad038ca66e4a3fe2adc83255d2b1830295ec385663ae7117e72f55f25982a
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README.md CHANGED
@@ -1,20 +1,21 @@
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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
@@ -27,9 +28,9 @@ model-index:
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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: 1.2309
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  - Wer: 56.6510
 
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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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  <!-- 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: 1.2309
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  - Wer: 56.6510
run_speech_recognition_seq2seq_streaming.py CHANGED
@@ -556,7 +556,7 @@ def main():
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  elif isinstance(train_dataloader.dataset, IterableDataset):
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  train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
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- model.config.dropout=0.3
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  # Initialize Trainer
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  trainer = Seq2SeqTrainer(
 
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  elif isinstance(train_dataloader.dataset, IterableDataset):
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  train_dataloader.dataset.set_epoch(train_dataloader.dataset._epoch + 1)
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+ model.config.dropout=0.1
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  # Initialize Trainer
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  trainer = Seq2SeqTrainer(