readme: ---
  language:
  - ml
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny ml - Bharat Ramanathan
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: ml
        split: test
      metrics:
      - type: wer
        value: 45.72
        name: WER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: ml_in
        split: test
      metrics:
      - type: wer
        value: 62.15
        name: WER
  ---
  
  <!-- 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 Tiny ml - Bharat Ramanathan
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1286
  - Wer: 106.9296
  
  ## 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: 32
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.5755        | 4.02  | 500  | 0.4241          | 81.2652 |
  | 0.4182        | 9.01  | 1000 | 0.3245          | 72.7494 |
  | 0.3387        | 14.01 | 1500 | 0.2914          | 67.2749 |
  | 0.2923        | 19.0  | 2000 | 0.2745          | 60.3406 |
  | 0.2596        | 24.0  | 2500 | 0.2645          | 58.2725 |
  | 0.2356        | 28.02 | 3000 | 0.2629          | 60.3406 |
  | 0.2167        | 33.01 | 3500 | 0.2647          | 59.9757 |
  | 0.2039        | 4.02  | 4000 | 0.2617          | 58.2725 |
  | 0.1938        | 9.01  | 4500 | 0.2644          | 58.2725 |
  | 0.1858        | 14.01 | 5000 | 0.2636          | 58.7591 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  