readme: ---
  language:
  - ml
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - thennal/imasc
  metrics:
  - wer
  model-index:
  - name: Whisper Large V2 Malayalam
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: ICFOSS Malayalam Speech Corpus
        type: thennal/imasc
        config: ml
        split: test
        args: ml
      metrics:
      - name: Wer
        type: wer
        value: 44.13793103448276
  ---
  
  <!-- 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 Malayalam
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ICFOSS Malayalam Speech Corpus dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0617
  - Wer: 44.1379
  - Cer: 9.6895
  
  ## 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: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 0.1071        | 0.13  | 500  | 0.1274          | 62.9885 | 15.0225 |
  | 0.0693        | 0.26  | 1000 | 0.1052          | 57.4713 | 13.0696 |
  | 0.054         | 0.39  | 1500 | 0.0902          | 48.0460 | 11.5173 |
  | 0.0494        | 0.51  | 2000 | 0.0774          | 46.4368 | 10.7912 |
  | 0.0446        | 0.64  | 2500 | 0.0722          | 46.8966 | 10.7161 |
  | 0.0463        | 0.77  | 3000 | 0.0699          | 46.2069 | 10.3405 |
  | 0.0347        | 0.9   | 3500 | 0.0662          | 43.6782 | 10.2404 |
  | 0.0233        | 1.03  | 4000 | 0.0688          | 45.7471 | 10.4407 |
  | 0.0226        | 1.16  | 4500 | 0.0642          | 44.5977 | 10.1152 |
  | 0.0194        | 1.28  | 5000 | 0.0617          | 44.1379 | 9.6895  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  