readme: ---
  language:
  - te
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - IndicSUPERB_train_validation_splits
  metrics:
  - wer
  model-index:
  - name: Whisper Small Telugu - Naga Budigam
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: IndicSUPERB train and validation splits
        type: IndicSUPERB train and validation splits
        config: None
        split: None
        args: 'config: te, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 38.14924740301039
  ---
  
  <!-- 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: 0.2875
  - Wer: 38.1492
  
  ## 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: 15000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2064        | 0.66  | 500   | 0.2053          | 60.1707 |
  | 0.1399        | 1.33  | 1000  | 0.1535          | 49.3269 |
  | 0.1093        | 1.99  | 1500  | 0.1365          | 44.5516 |
  | 0.0771        | 2.66  | 2000  | 0.1316          | 42.1136 |
  | 0.0508        | 3.32  | 2500  | 0.1395          | 41.1384 |
  | 0.0498        | 3.99  | 3000  | 0.1386          | 40.5395 |
  | 0.0302        | 4.65  | 3500  | 0.1529          | 40.9529 |
  | 0.0157        | 5.32  | 4000  | 0.1719          | 40.6667 |
  | 0.0183        | 5.98  | 4500  | 0.1723          | 40.3646 |
  | 0.0083        | 6.65  | 5000  | 0.1911          | 40.4335 |
  | 0.0061        | 7.31  | 5500  | 0.2109          | 40.4176 |
  | 0.0055        | 7.98  | 6000  | 0.2075          | 39.7021 |
  | 0.0039        | 8.64  | 6500  | 0.2186          | 40.2639 |
  | 0.0026        | 9.31  | 7000  | 0.2254          | 39.1032 |
  | 0.0035        | 9.97  | 7500  | 0.2289          | 39.2834 |
  | 0.0016        | 10.64 | 8000  | 0.2332          | 39.1456 |
  | 0.0016        | 11.3  | 8500  | 0.2395          | 39.4371 |
  | 0.0016        | 11.97 | 9000  | 0.2447          | 39.2410 |
  | 0.0009        | 12.63 | 9500  | 0.2548          | 38.7799 |
  | 0.0008        | 13.3  | 10000 | 0.2551          | 38.7481 |
  | 0.0008        | 13.96 | 10500 | 0.2621          | 38.8276 |
  | 0.0007        | 14.63 | 11000 | 0.2633          | 38.6686 |
  | 0.0003        | 15.29 | 11500 | 0.2711          | 38.4566 |
  | 0.0005        | 15.96 | 12000 | 0.2772          | 38.7852 |
  | 0.0001        | 16.62 | 12500 | 0.2771          | 38.2658 |
  | 0.0001        | 17.29 | 13000 | 0.2808          | 38.2393 |
  | 0.0001        | 17.95 | 13500 | 0.2815          | 38.1810 |
  | 0.0           | 18.62 | 14000 | 0.2854          | 38.2022 |
  | 0.0           | 19.28 | 14500 | 0.2872          | 38.1333 |
  | 0.0           | 19.95 | 15000 | 0.2875          | 38.1492 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  