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sew-d-small-100k-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: 1.7541
  • Wer: 0.8061

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
2.7718 4.14 600 2.7787 1.0
2.6711 4.83 700 2.6401 0.9786
2.6403 5.52 800 2.5435 1.0392
2.4052 6.21 900 2.4580 1.0706
2.1708 6.9 1000 2.2800 1.0090
2.2555 7.59 1100 2.1493 0.9579
2.3673 8.28 1200 2.0709 0.9051
2.091 8.97 1300 2.0258 0.8926
1.8433 9.66 1400 1.9645 0.8243
1.6824 10.34 1500 1.9211 0.8707
2.2282 11.03 1600 1.8914 0.8695
1.9027 11.72 1700 1.8718 0.8343
1.6303 12.41 1800 1.8646 0.8232
1.648 13.1 1900 1.8297 0.8177
2.0429 13.79 2000 1.8127 0.8642
1.8833 14.48 2100 1.8005 0.8307
1.5996 15.17 2200 1.7926 0.8467
1.4876 15.86 2300 1.7795 0.8341
1.8925 16.55 2400 1.7716 0.8199
1.814 17.24 2500 1.7846 0.8086
1.536 17.93 2600 1.7655 0.8019
1.4476 18.62 2700 1.7599 0.8070
1.7629 19.31 2800 1.7589 0.8119
1.7646 20.0 2900 1.7541 0.8061

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-timit