readme: ---
  language:
  - hi
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Hindi - Shripad Bhat
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: hi
        split: test
        args: hi
      metrics:
      - name: Wer
        type: wer
        value: 21.451908746990714
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: FLEURS
        type: google/fleurs
        config: hi_in
        split: test
        args: hi
      metrics:
      - name: Wer
        type: wer
        value: 22.11
  ---
  
  <!-- 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 Hindi - Shripad Bhat
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3909
  - Wer: 21.4519
  
  ## 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
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.4337        | 0.73  | 100  | 0.4874          | 47.5868 |
  | 0.1894        | 1.47  | 200  | 0.3264          | 23.9482 |
  | 0.1007        | 2.21  | 300  | 0.3101          | 22.5267 |
  | 0.0984        | 2.94  | 400  | 0.3064          | 21.5723 |
  | 0.0555        | 3.67  | 500  | 0.3325          | 22.0251 |
  | 0.029         | 4.41  | 600  | 0.3439          | 21.4863 |
  | 0.0163        | 5.15  | 700  | 0.3668          | 21.6468 |
  | 0.0153        | 5.88  | 800  | 0.3756          | 21.4662 |
  | 0.0081        | 6.62  | 900  | 0.3888          | 21.5035 |
  | 0.0059        | 7.35  | 1000 | 0.3909          | 21.4519 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  