readme: ---
  language:
  - te
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Base Te - Bharat Ramanathan
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: te_in
        split: test
      metrics:
      - type: wer
        value: 39.09
        name: WER
  ---
  
  <!-- 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 Base Te - Bharat Ramanathan
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2455
  - Wer: 42.6485
  
  ## 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: 96
  - eval_batch_size: 64
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.6341        | 0.1   | 500  | 0.3894          | 60.7108 |
  | 0.349         | 0.2   | 1000 | 0.3081          | 52.0935 |
  | 0.2792        | 0.3   | 1500 | 0.2874          | 49.7079 |
  | 0.2433        | 0.4   | 2000 | 0.2720          | 47.5657 |
  | 0.2224        | 1.06  | 2500 | 0.2632          | 45.2288 |
  | 0.2058        | 1.16  | 3000 | 0.2529          | 44.3038 |
  | 0.1944        | 1.26  | 3500 | 0.2519          | 44.5959 |
  | 0.1869        | 1.36  | 4000 | 0.2475          | 43.7196 |
  | 0.1811        | 2.03  | 4500 | 0.2451          | 43.3301 |
  | 0.1775        | 2.13  | 5000 | 0.2455          | 42.6485 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  