readme: ---
  language:
  - ta
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper tiny Ta example - Bharat Ramanathan
    results: []
  ---
  
  <!-- 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 tiny Ta example - Bharat Ramanathan
  
  This model is a fine-tuned version of [parambharat/whisper-tiny-ta](https://huggingface.co/parambharat/whisper-tiny-ta) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4016
  - Wer: 36.5217
  
  ## 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: 32
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 25
  - training_steps: 100
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.304         | 12.01 | 25   | 0.3614          | 31.7391 |
  | 0.1826        | 24.02 | 50   | 0.3851          | 35.2174 |
  | 0.1346        | 37.01 | 75   | 0.3999          | 37.8261 |
  | 0.1096        | 49.02 | 100  | 0.4016          | 36.5217 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  