readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - whisper-event
  metrics:
  - wer
  model-index:
  - name: openai/whisper-medium
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 ca
        type: mozilla-foundation/common_voice_11_0
        args: 'config: ml, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 8.282966640983934
  ---
  
  <!-- 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 is an automatic speech recognition model that also does punctuation and casing. Vegeu [projecte de millora dels models Whisper](https://www.softcatala.org/projectes/millora-del-catala-dels-models-del-reconeixement-de-la-parla-whisper/) (Catalan).
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 ca dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2029
  - Wer: 8.3235
  
  ## 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: 2
  - eval_batch_size: 1
  - 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: 20000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2652        | 0.1   | 2000  | 0.3469          | 15.3537 |
  | 0.3273        | 0.2   | 4000  | 0.3151          | 14.1141 |
  | 0.2696        | 0.3   | 6000  | 0.2955          | 13.2472 |
  | 0.1725        | 0.4   | 8000  | 0.2787          | 11.6834 |
  | 0.1741        | 0.5   | 10000 | 0.2648          | 11.0088 |
  | 0.2037        | 0.6   | 12000 | 0.2470          | 10.1909 |
  | 0.1586        | 0.7   | 14000 | 0.2333          | 9.4096  |
  | 0.1548        | 0.8   | 16000 | 0.2184          | 8.9724  |
  | 0.1799        | 1.08  | 18000 | 0.2064          | 8.2830  |
  | 0.1165        | 1.18  | 20000 | 0.2029          | 8.3235  |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.10.0+cu102
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  