readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - whisper-event
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: whisper-small-el
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 el
        type: mozilla-foundation/common_voice_11_0
        config: el
        split: test
        args: el
      metrics:
      - name: Wer
        type: wer
        value: 25.696508172362552
  ---
  
  # Whisper Small - Greek (el)
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 el dataset 
  for transcription in Greek.
  It achieves the following results on the evaluation set:
  
  - train_loss: 0.0615
  - Wer: 20.2080
  
  
  ### Training results
  
  Upon completion of training the best model was reloaded and tested with the following results extracted from the stdout log:
  ```
  Loading best model from ./whisper-small-el/checkpoint-5000 (score: 20.208023774145616).
  
  {'train_runtime': 73232.697,
  'train_samples_per_second': 4.37,
  'train_steps_per_second': 0.068,
  'train_loss': 0.06146362095708027,
  'epoch': 94.34}
  
  TrainOutput(global_step=5000,
      training_loss=0.06146362095708027,
      metrics={'train_runtime': 73232.697,
          'train_samples_per_second': 4.37,
          'train_steps_per_second': 0.068,
          'train_loss': 0.06146362095708027,
          'epoch': 94.34})
  ```
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.12.1
  