readme: ---
  language:
  - el
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: whisper-sm-el-intlv-xl
    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: 19.48365527488856
  ---
  
  
  # whisper-sm-el-intlv-xl
  
  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) and the google/fleurs (el_gr) datasets.
  It achieves the following results on the evaluation set:
  - Loss: 0.4725
  - Wer: 19.4837
  
  ## Model description
  
  The model was trained over 10000 steps on translation from Greek to English. 
  
  ## Intended uses & limitations
  
  This model was part of the Whisper Finetuning Event (Dec 2022) and was used primarily to compare relative improvements between transcription and translation tasks.
  
  ## Training and evaluation data
  
  The training datasets combined examples from both train and evaluation splits and use the train split of the mozilla-foundation/common_voice_11_0 (el) dataset for evaluation and selection of the best checkpoint. 
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 8.5e-06
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0545        | 2.49  | 1000  | 0.2891          | 22.4926 |
  | 0.0093        | 4.98  | 2000  | 0.3927          | 20.1337 |
  | 0.0018        | 7.46  | 3000  | 0.4031          | 20.1616 |
  | 0.001         | 9.95  | 4000  | 0.4209          | 19.6880 |
  | 0.0008        | 12.44 | 5000  | 0.4498          | 20.0966 |
  | 0.0005        | 14.93 | 6000  | 0.4725          | 19.4837 |
  | 0.0002        | 17.41 | 7000  | 0.4917          | 19.5951 |
  | 0.0001        | 19.9  | 8000  | 0.5050          | 19.6230 |
  | 0.0001        | 22.39 | 9000  | 0.5146          | 19.5672 |
  | 0.0001        | 24.88 | 10000 | 0.5186          | 19.4837 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.12.1
  