readme: ---
  language:
  - ta
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Small Ta - Bharat Ramanathan
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: ta_in
        split: test
      metrics:
      - type: wer
        value: 15.8
        name: WER
    - 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: ta
        split: test
      metrics:
      - type: wer
        value: 11.15
        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 Small Ta - Bharat Ramanathan
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1803
  - Wer: 17.1456
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3374        | 0.1   | 500  | 0.2579          | 23.3804 |
  | 0.29          | 0.2   | 1000 | 0.2260          | 20.9937 |
  | 0.2522        | 0.3   | 1500 | 0.2139          | 20.0682 |
  | 0.2338        | 0.4   | 2000 | 0.2025          | 19.6785 |
  | 0.223         | 0.5   | 2500 | 0.1979          | 18.3147 |
  | 0.211         | 0.6   | 3000 | 0.1927          | 17.8276 |
  | 0.2032        | 0.7   | 3500 | 0.1865          | 17.3892 |
  | 0.1978        | 0.8   | 4000 | 0.1839          | 17.5353 |
  | 0.1972        | 0.9   | 4500 | 0.1812          | 17.0969 |
  | 0.1894        | 1.0   | 5000 | 0.1803          | 17.1456 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  