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whisper-small-tamil

This model is a fine-tuned version of openai/whisper-small on the google/fleurs dataset for Tamil. It achieves the following results on the evaluation set:

  • Loss: 0.42
  • Wer: 15.02

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • 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
0.0882 2.27 500 0.2674 16.7354
0.0026 11.76 1000 0.3508 15.3720
0.0012 17.64 1500 0.3920 15.6156
0.0009 23.53 2000 0.4076 15.4284
0.0002 29.41 2500 0.4268 15.0215

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train steja/whisper-small-tamil

Evaluation results