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 Medium Greek - Robust
    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: 21.684621099554235
  ---
  
  <!-- 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 Medium Greek - Robust
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 el dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3168
  - Wer: 21.6846
  
  ## 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: 8
  - eval_batch_size: 4
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3865        | 1.17  | 500  | 0.5842          | 51.4487 |
  | 0.2302        | 2.35  | 1000 | 0.4861          | 39.3202 |
  | 0.1321        | 3.52  | 1500 | 0.4536          | 37.4257 |
  | 0.0916        | 4.69  | 2000 | 0.4103          | 39.6824 |
  | 0.0497        | 5.87  | 2500 | 0.4101          | 29.1883 |
  | 0.03          | 7.04  | 3000 | 0.4121          | 28.0089 |
  | 0.0156        | 8.22  | 3500 | 0.3842          | 26.7459 |
  | 0.0037        | 9.39  | 4000 | 0.3433          | 28.7054 |
  | 0.0008        | 10.56 | 4500 | 0.3244          | 21.8332 |
  | 0.0006        | 11.74 | 5000 | 0.3178          | 21.5267 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.7.1
  - Tokenizers 0.12.1
  