readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: openai/whisper-medium
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: common_voice_11_0
        type: common_voice_11_0
        config: ga-IE
        split: test
        args: ga-IE
      metrics:
      - name: Wer
        type: wer
        value: 35.22067363530778
  ---
  
  <!-- 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. -->
  
  # openai/whisper-medium
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1422
  - Wer: 35.2207
  
  ## 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-05
  - train_batch_size: 16
  - 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: 7000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1137        | 4.02  | 1000 | 0.9072          | 40.0987 |
  | 0.0153        | 9.02  | 2000 | 1.0351          | 38.7631 |
  | 0.0042        | 14.01 | 3000 | 1.0507          | 36.4402 |
  | 0.0013        | 19.0  | 4000 | 1.0924          | 36.2660 |
  | 0.0003        | 23.02 | 5000 | 1.1422          | 35.2207 |
  | 0.0001        | 28.02 | 6000 | 1.1688          | 35.3368 |
  | 0.0001        | 33.01 | 7000 | 1.1768          | 35.5110 |
  
  
  ### Framework versions
  
  - Transformers 4.27.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.9.1.dev0
  - Tokenizers 0.13.2
  