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sew-d-small-100k-ft-timit-2

This model is a fine-tuned version of asapp/sew-d-small-100k on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7357
  • Wer: 0.7935

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.1554 0.69 100 4.0531 1.0
2.9584 1.38 200 2.9775 1.0
2.9355 2.07 300 2.9412 1.0
2.9048 2.76 400 2.9143 1.0
2.8568 3.45 500 2.8786 1.0
2.7248 4.14 600 2.7553 0.9833
2.6124 4.83 700 2.5874 1.0511
2.5463 5.52 800 2.4630 1.0883
2.3302 6.21 900 2.3948 1.0651
2.0669 6.9 1000 2.2228 0.9920
2.1991 7.59 1100 2.0815 0.9185
2.293 8.28 1200 2.0229 0.8674
2.0366 8.97 1300 1.9590 0.9165
1.767 9.66 1400 1.9129 0.8125
1.6222 10.34 1500 1.8868 0.8259
2.173 11.03 1600 1.8691 0.8661
1.8614 11.72 1700 1.8388 0.8250
1.5928 12.41 1800 1.8528 0.7772
1.5978 13.1 1900 1.8002 0.7892
1.9886 13.79 2000 1.7848 0.8448
1.8042 14.48 2100 1.7819 0.8156
1.5488 15.17 2200 1.7615 0.8228
1.4468 15.86 2300 1.7565 0.7946
1.8153 16.55 2400 1.7537 0.8341
1.77 17.24 2500 1.7527 0.7958
1.4742 17.93 2600 1.7592 0.7850
1.4088 18.62 2700 1.7421 0.8149
1.7066 19.31 2800 1.7382 0.7977
1.7068 20.0 2900 1.7357 0.7935

Framework versions

  • Transformers 4.12.0.dev0
  • Pytorch 1.8.1
  • Datasets 1.14.1.dev0
  • Tokenizers 0.10.3
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Dataset used to train patrickvonplaten/sew-d-small-100k-ft-timit-2