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Whisper Small Bemba - Beijuka Bruno

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

  • Loss: 0.5013
  • Wer: 0.3531
  • Cer: 0.1008

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.025
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.9062 1.0 5914 0.4964 0.4258 0.1059
0.5025 2.0 11828 0.4104 0.3567 0.0887
0.4079 3.0 17742 0.3767 0.3252 0.0827
0.3239 4.0 23656 0.3676 0.3133 0.0804
0.2438 5.0 29570 0.3798 0.3219 0.0846
0.1655 6.0 35484 0.4092 0.3124 0.0787
0.0986 7.0 41398 0.4579 0.3251 0.0845
0.0554 8.0 47312 0.4980 0.3231 0.0844
0.0342 9.0 53226 0.5362 0.3174 0.0820
0.0255 10.0 59140 0.5647 0.3150 0.0810
0.021 11.0 65054 0.5882 0.3153 0.0797
0.0184 12.0 70968 0.6067 0.3162 0.0805
0.0161 13.0 76882 0.6337 0.3192 0.0842
0.0146 14.0 82796 0.6493 0.3138 0.0819

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.1.0+cu118
  • Datasets 3.0.1
  • Tokenizers 0.20.1
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