readme: ---
  language:
  - as
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Assamese - Drishti Sharma
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: as
        split: test
        args: as
      metrics:
      - name: Wer
        type: wer
        value: 30.650219527493206
  ---
  
  <!-- 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 Assamese - Drishti Sharma
  
  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: 0.5164
  - Wer: 30.6502
  
  ## 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: 4
  - 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: 150
  - training_steps: 500
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 1.1539        | 3.02  | 50   | 0.7835          | 89.0863 |
  | 0.2089        | 7.0   | 100  | 0.3041          | 37.7378 |
  | 0.0428        | 10.02 | 150  | 0.3760          | 33.9118 |
  | 0.0141        | 14.01 | 200  | 0.4400          | 31.6538 |
  | 0.0059        | 17.02 | 250  | 0.4472          | 31.2774 |
  | 0.0022        | 21.01 | 300  | 0.4696          | 31.0475 |
  | 0.0005        | 24.03 | 350  | 0.5032          | 31.2983 |
  | 0.0003        | 28.02 | 400  | 0.5051          | 30.7129 |
  | 0.0003        | 32.0  | 450  | 0.5137          | 30.7338 |
  | 0.0003        | 35.02 | 500  | 0.5164          | 30.6502 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  