readme: ---
  language:
  - te
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - Chai_Bisket_Stories_16-08-2021_14-17
  metrics:
  - wer
  model-index:
  - name: Whisper Small Telugu - Naga Budigam
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Chai_Bisket_Stories_16-08-2021_14-17
        type: Chai_Bisket_Stories_16-08-2021_14-17
        config: None
        split: None
        args: 'config: te, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 77.48711850971065
  ---
  
  <!-- 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 Telugu - Naga Budigam
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Chai_Bisket_Stories_16-08-2021_14-17 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7063
  - Wer: 77.4871
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.2933        | 2.62  | 500  | 0.3849          | 86.6429 |
  | 0.0692        | 5.24  | 1000 | 0.3943          | 82.7190 |
  | 0.0251        | 7.85  | 1500 | 0.4720          | 82.4415 |
  | 0.0098        | 10.47 | 2000 | 0.5359          | 81.6092 |
  | 0.0061        | 13.09 | 2500 | 0.5868          | 75.9413 |
  | 0.0025        | 15.71 | 3000 | 0.6235          | 76.6944 |
  | 0.0009        | 18.32 | 3500 | 0.6634          | 78.3987 |
  | 0.0005        | 20.94 | 4000 | 0.6776          | 77.1700 |
  | 0.0002        | 23.56 | 4500 | 0.6995          | 78.2798 |
  | 0.0001        | 26.18 | 5000 | 0.7063          | 77.4871 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  