readme: ---
  language:
  - el
  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: 24.322065378900444
  ---
  
  <!-- 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 [whisper-el-medium-augmented](https://huggingface.co/whisper-el-medium-augmented) on the mozilla-foundation/common_voice_11_0 el dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4312
  - Wer: 24.3221
  
  ## 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: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0905        | 2.35  | 1000  | 0.5419          | 37.8343 |
  | 0.0552        | 4.69  | 2000  | 0.5118          | 34.6954 |
  | 0.0329        | 7.04  | 3000  | 0.5332          | 32.3180 |
  | 0.0219        | 9.39  | 4000  | 0.5185          | 30.1913 |
  | 0.0161        | 11.74 | 5000  | 0.4908          | 32.3366 |
  | 0.0063        | 14.08 | 6000  | 0.4741          | 28.4733 |
  | 0.0015        | 16.43 | 7000  | 0.4400          | 26.3187 |
  | 0.001         | 18.78 | 8000  | 0.4428          | 25.5293 |
  | 0.0001        | 21.13 | 9000  | 0.4382          | 25.2043 |
  | 0.0014        | 23.47 | 10000 | 0.4328          | 24.3221 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.7.1
  - Tokenizers 0.12.1
  