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: 16.493313521545318
  ---
  
  <!-- 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 Farsipal and  El Greco
  
  This model is a fine-tuned version of [emilios/whisper-sm-farsipal-e5](https://huggingface.co/emilios/whisper-sm-farsipal-e5) on the mozilla-foundation/common_voice_11_0,google/fleurs el,el_gr dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5015
  - Wer: 16.4933
  
  ## 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: 5000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0004        | 2.49  | 1000 | 0.4797          | 16.7348 |
  | 0.0003        | 4.98  | 2000 | 0.4895          | 16.5397 |
  | 0.0002        | 7.46  | 3000 | 0.4963          | 16.5119 |
  | 0.0002        | 9.95  | 4000 | 0.5015          | 16.4933 |
  | 0.0002        | 12.44 | 5000 | 0.5034          | 16.5676 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 2.0.0.dev20221216+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  