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 Large V2 Farsipal and El Greco
    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: 9.110326894502228
  ---
  
  <!-- 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 Large V2 Farsipal and El Greco
  
  This model is a fine-tuned version of [emilios/whisper-lg-v2-parsifal-el-0](https://huggingface.co/emilios/whisper-lg-v2-parsifal-el-0) on the mozilla-foundation/common_voice_11_0 el dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2866
  - Wer: 9.1103
  
  ## 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: 3e-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: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.0281        | 9.35  | 1000 | 0.2515          | 9.5561 |
  | 0.0131        | 18.69 | 2000 | 0.2866          | 9.1103 |
  | 0.0069        | 28.04 | 3000 | 0.3118          | 9.2403 |
  | 0.004         | 37.38 | 4000 | 0.3279          | 9.3796 |
  | 0.0025        | 46.73 | 5000 | 0.3464          | 9.3146 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221216+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  