readme: ---
  language:
  - ta
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  model-index:
  - name: whisper-small-tamil
    results: 
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ta_in
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 15.021
  ---
  
  <!-- 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-tamil
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset for Tamil.
  It achieves the following results on the evaluation set:
  - Loss: 0.42
  - Wer: 15.02
  ## 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: 8
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0882        | 2.27  | 500  | 0.2674          | 16.7354 |
  | 0.0026        | 11.76 | 1000 | 0.3508          | 15.3720 |
  | 0.0012        | 17.64 | 1500 | 0.3920          | 15.6156 |
  | 0.0009        | 23.53 | 2000 | 0.4076          | 15.4284 |
  | 0.0002        | 29.41 | 2500 | 0.4268          | 15.0215 |
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  