readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - facebook/multilingual_librispeech
  metrics:
  - wer
  model-index:
  - name: Whisper largeV2 dutch MLS
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: facebook/multilingual_librispeech dutch
        type: facebook/multilingual_librispeech
        config: dutch
        split: test
        args: dutch
      metrics:
      - name: Wer
        type: wer
        value: 10.591602311347534
  ---
  
  <!-- 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 largeV2 dutch MLS
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the facebook/multilingual_librispeech dutch dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2031
  - Wer: 10.5916
  
  ## Model description
  
  The model is fine-tuned for 4000 updates/steps on multilingual librispeech Dutch train data.
  
  - Zero-shot                        - 9.3 (MLS Dutch test)
  - Fine-tune MLS Dutch train        - 10.59 (MLS Dutch test)
  
  Even after fine-tuning the model is doing worse than the zero-shot model.
  
  
  ## 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: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 4000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.2515        | 0.25  | 1000 | 0.2579          | 12.9776 |
  | 0.24          | 0.5   | 2000 | 0.2361          | 11.2418 |
  | 0.1308        | 0.75  | 3000 | 0.2335          | 10.7503 |
  | 0.1072        | 1.0   | 4000 | 0.2031          | 10.5916 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  