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

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: 1.7482
  • Wer: 0.7987

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
4.2068 0.69 100 4.0802 1.0
2.9805 1.38 200 2.9792 1.0
2.9781 2.07 300 2.9408 1.0
2.9655 2.76 400 2.9143 1.0
2.8953 3.45 500 2.8775 1.0
2.7719 4.14 600 2.7815 0.9999
2.6531 4.83 700 2.6375 1.0065
2.6425 5.52 800 2.5602 1.0210
2.3963 6.21 900 2.4665 1.0591
2.1447 6.9 1000 2.2792 0.9848
2.2719 7.59 1100 2.2237 0.9465
2.3629 8.28 1200 2.1058 0.8907
2.0913 8.97 1300 2.0113 0.9070
1.8334 9.66 1400 1.9466 0.8177
1.6608 10.34 1500 1.9217 0.8698
2.2194 11.03 1600 1.9091 0.8727
1.9002 11.72 1700 1.8746 0.8332
1.6268 12.41 1800 1.8782 0.7951
1.6455 13.1 1900 1.8230 0.8225
2.0308 13.79 2000 1.8067 0.8560
1.855 14.48 2100 1.8129 0.8177
1.5901 15.17 2200 1.7891 0.8367
1.4848 15.86 2300 1.7821 0.8201
1.8754 16.55 2400 1.7700 0.8137
1.7975 17.24 2500 1.7795 0.8171
1.5194 17.93 2600 1.7605 0.7977
1.4374 18.62 2700 1.7529 0.7978
1.7498 19.31 2800 1.7522 0.8023
1.7452 20.0 2900 1.7482 0.7987

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