Whisper Base Bengali

This model is a fine-tuned version of arun100/whisper-base-bn on the google/fleurs bn_in dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2509
  • Wer: 43.6760

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-07
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2889 79.0 1000 0.2730 45.0242
0.2527 159.0 2000 0.2593 44.4617
0.2306 239.0 3000 0.2539 44.0616
0.2191 319.0 4000 0.2515 43.7367
0.2164 399.0 5000 0.2509 43.6760

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.2.dev0
  • Tokenizers 0.15.0
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