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Rakib
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whisper-small-bn-crblp

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Bengali
whisper
whisper-event
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Whisper Small - Mohammed Rakib

This model is a fine-tuned version of openai/whisper-small on the common-voice-11, the google-fleurs, the openslr53 and the crblp speech corpus datasets. It achieves the following results on the evaluation set:

  • Loss: 0.0617
  • Cer: 5.4436
  • Wer: 9.6538

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: 4
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 8000
  • training_steps: 40000

Training results

Training Loss Epoch Step Validation Loss Cer Wer
0.5361 0.13 1000 0.4043 22.6599 44.0521
0.2881 0.26 2000 0.2217 16.3939 32.4894
0.2265 0.38 3000 0.1728 13.0425 25.9637
0.1974 0.51 4000 0.1430 11.3260 22.3187
0.1591 0.64 5000 0.1255 10.0167 19.5115
0.1504 0.77 6000 0.1102 8.8333 17.1919
0.1259 0.89 7000 0.1003 8.1863 15.8576
0.1184 1.02 8000 0.0940 7.7868 14.9110
0.1099 1.15 9000 0.0885 7.3675 13.9444
0.1075 1.28 10000 0.0830 6.9648 13.2008
0.095 1.41 11000 0.0789 6.6969 12.6776
0.0943 1.53 12000 0.0766 6.3765 11.9896
0.0923 1.66 13000 0.0731 6.1784 11.7203
0.0824 1.79 14000 0.0699 5.9267 11.1632
0.0756 1.92 15000 0.0683 5.6305 10.6327
0.0634 2.04 16000 0.0671 5.6905 10.6947
0.0618 2.17 17000 0.0662 5.5107 10.2926
0.0679 2.3 18000 0.0643 5.4948 10.1792
0.0589 2.43 19000 0.0647 5.5201 10.1881
0.0623 2.56 20000 0.0633 5.2731 9.8449
0.0558 2.68 21000 0.0623 5.4211 10.0267
0.0564 2.81 22000 0.0617 5.4553 9.9893
0.0552 2.94 23000 0.0607 5.3860 9.7778
0.0403 3.07 24000 0.0621 5.7297 10.0382
0.0406 3.19 25000 0.0617 5.4436 9.6538
0.041 3.32 26000 0.0611 6.0867 10.3834
0.0388 3.45 27000 0.0614 6.1641 10.3890
0.0383 3.58 28000 0.0611 6.1460 10.3537
0.0401 3.71 29000 0.0603 6.9576 11.0697
0.0343 3.83 30000 0.0613 7.1918 11.2243
0.0357 3.96 31000 0.0603 7.3128 11.3313
0.0313 4.09 32000 0.0624 7.3871 11.3861
0.0281 4.22 33000 0.0626 7.8705 11.8248
0.0298 4.34 34000 0.0629 8.3360 12.2368
0.0282 4.47 35000 0.0627 8.7840 12.6270

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.10.2.dev0
  • Tokenizers 0.13.2
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Datasets used to train Rakib/whisper-small-bn-crblp

Space using Rakib/whisper-small-bn-crblp 1

Evaluation results

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