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 small Greek Farsipal and  El Greco
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr
        type: mozilla-foundation/common_voice_11_0,google/fleurs
        config: el
        split: None
      metrics:
      - name: Wer
        type: wer
        value: 17.199108469539375
  ---
  
  <!-- 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 Farsioal and  El Greco
  
  This model is a fine-tuned version of [emilios/whisper-sm-el-farsipal-e4](https://huggingface.co/emilios/whisper-sm-el-farsipal-e4) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4871
  - Wer: 17.1991
  
  ## 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: 1e-06
  - train_batch_size: 32
  - eval_batch_size: 16
  - seed: 42
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 20000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1259        | 2.49  | 1000  | 0.4834          | 18.3692 |
  | 0.1002        | 4.49  | 2000  | 0.4604          | 17.8027 |
  | 0.1096        | 6.98  | 3000  | 0.4553          | 17.8770 |
  | 0.0885        | 9.46  | 4000  | 0.4551          | 17.9606 |
  | 0.0675        | 11.95 | 5000  | 0.4631          | 17.9049 |
  | 0.0675        | 14.44 | 6000  | 0.4619          | 17.9049 |
  | 0.0645        | 16.93 | 7000  | 0.4678          | 17.6727 |
  | 0.0535        | 19.41 | 8000  | 0.4685          | 17.6634 |
  | 0.039         | 21.49 | 9000  | 0.4746          | 17.6727 |
  | 0.0447        | 23.98 | 10000 | 0.4761          | 17.6634 |
  | 0.0393        | 26.46 | 11000 | 0.4792          | 17.7656 |
  | 0.0308        | 28.95 | 12000 | 0.4851          | 17.8678 |
  | 0.0301        | 31.44 | 13000 | 0.4846          | 17.4499 |
  | 0.031         | 33.93 | 14000 | 0.4849          | 17.8306 |
  | 0.0263        | 36.41 | 15000 | 0.4880          | 17.6170 |
  | 0.0256        | 38.9  | 16000 | 0.4871          | 17.1991 |
  | 0.0236        | 41.39 | 17000 | 0.4883          | 17.2641 |
  | 0.0195        | 43.88 | 18000 | 0.4880          | 17.5706 |
  | 0.0193        | 46.36 | 19000 | 0.4993          | 17.7285 |
  | 0.0161        | 48.85 | 20000 | 0.4968          | 17.8306 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221216+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  