readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
  - automatic-speech-recognition
  - greek
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: whisper-md-el-intlv-xs
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: el
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 11.3670
  ---
  
  
  # whisper-md-el-intlv-xs
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on interleaved mozilla-foundation/common_voice_11_0 (el) and the google/fleurs (el_gr) datasets. It achieves the following results on the mozilla-foundation/common_voice_11_0 test evaluation set:
  - Loss: 0.4168
  - Wer: 11.3670
  
  ## Model description
  
  This model is trained over the two interleaved datasets in the Greek language. Testing used only the common_voice_11_0 (el) test split.
  
  ## Intended uses & limitations
  
  The model was trained for transcription in Greek 
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 8e-06
  - train_batch_size: 32
  - 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: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0251        | 2.49  | 1000  | 0.2216          | 12.5836 |
  | 0.0051        | 4.98  | 2000  | 0.2874          | 12.2957 |
  | 0.0015        | 7.46  | 3000  | 0.3281          | 11.9056 |
  | 0.0017        | 9.95  | 4000  | 0.3178          | 12.5929 |
  | 0.0008        | 12.44 | 5000  | 0.3449          | 11.9799 |
  | 0.0001        | 14.93 | 6000  | 0.3638          | 11.7106 |
  | 0.0001        | 17.41 | 7000  | 0.3910          | 11.4970 |
  | 0.0           | 19.9  | 8000  | 0.4042          | 11.3949 |
  | 0.0           | 22.39 | 9000  | 0.4129          | 11.4134 |
  | 0.0           | 24.88 | 10000 | 0.4168          | 11.3670 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  