readme: ---
  language:
  - ta
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny Ta - Bharat Ramanathan
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: ta
        split: test
        args: ta
      metrics:
      - type: wer
        value: 30.102694404742998
        name: Wer
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: ta_in
        split: test
      metrics:
      - type: wer
        value: 26.07
        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 Tiny Ta - Bharat Ramanathan
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3096
  - Wer: 30.1027
  
  ## 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: 1000
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.5622        | 0.2   | 1000  | 0.4460          | 41.4141 |
  | 0.4151        | 0.4   | 2000  | 0.3657          | 35.1390 |
  | 0.3727        | 0.6   | 3000  | 0.3417          | 33.1723 |
  | 0.3519        | 0.8   | 4000  | 0.3252          | 31.9497 |
  | 0.3354        | 1.0   | 5000  | 0.3192          | 31.3997 |
  | 0.3492        | 0.1   | 6000  | 0.3283          | 31.6966 |
  | 0.3229        | 0.2   | 7000  | 0.3211          | 31.1339 |
  | 0.3193        | 0.3   | 8000  | 0.3138          | 30.5161 |
  | 0.314         | 0.4   | 9000  | 0.3112          | 30.1832 |
  | 0.3087        | 0.5   | 10000 | 0.3096          | 30.1027 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  