readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Greek - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: 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:
      - type: wer
        value: 24.52637444279346
        name: Wer
      - type: wer
        value: 20.42
        name: WER
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # Whisper Small Greek - Robust
  
  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.
  It achieves the following results on the evaluation set:
  - Loss: 0.3605
  - Wer: 24.5264
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.2223        | 2.35  | 500  | 0.4403          | 37.9922 |
  | 0.0908        | 4.69  | 1000 | 0.4041          | 35.6519 |
  | 0.0465        | 7.04  | 1500 | 0.4189          | 34.3053 |
  | 0.0168        | 9.39  | 2000 | 0.3972          | 29.9127 |
  | 0.0118        | 11.74 | 2500 | 0.4043          | 28.9933 |
  | 0.0053        | 14.08 | 3000 | 0.3968          | 28.5940 |
  | 0.0032        | 16.43 | 3500 | 0.3664          | 25.6779 |
  | 0.0009        | 18.78 | 4000 | 0.3665          | 26.2444 |
  | 0.0003        | 21.13 | 4500 | 0.3620          | 25.2879 |
  | 0.0004        | 23.47 | 5000 | 0.3570          | 24.8607 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  