Whisper Small Tamil

This model is a fine-tuned version of openai/whisper-small on the Common Voice 24.0 - Tamil dataset.

Model description

The model converts spoken Tamil audio into written Tamil text. It was fine-tuned using the Mozilla Common Voice 24.0 Tamil dataset.

  • Base model: openai/whisper-small
  • Language: Tamil (ta)
  • Task: Speech-to-text (transcription)

Intended uses & limitations

More information needed

Training and evaluation data

The model was fine-tuned on:

  • Dataset: Mozilla Common Voice 24.0 – Tamil
  • Type: Read, crowd-sourced speech
  • Audio: 16 kHz mono
  • Text: Tamil transcriptions
  • Splits: Train / validation Common Voice contains speech from a diverse set of speakers, but may still include demographic and accent imbalances. It skews toward younger male speakers.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 2000
  • mixed_precision_training: Native AMP

Training results

Final Training Loss = 0.130500
CER (Character Error Rate) = 0.4946198117007057

Framework versions

  • Transformers 4.52.0
  • Pytorch 2.9.0+cu126
  • Datasets 4.4.2
  • Tokenizers 0.21.4
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