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unispeech-sat-base-timit-ft

This model is a fine-tuned version of microsoft/unispeech-sat-base on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6712
  • Wer: 0.4101

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
3.2582 0.69 100 3.1651 1.0
2.9542 1.38 200 2.9567 1.0
2.9656 2.07 300 2.9195 1.0
2.8946 2.76 400 2.8641 1.0
1.9305 3.45 500 1.7680 1.0029
1.0134 4.14 600 1.0184 0.6942
0.8355 4.83 700 0.7769 0.6080
0.8724 5.52 800 0.7182 0.6035
0.5619 6.21 900 0.6823 0.5406
0.4247 6.9 1000 0.6279 0.5237
0.4257 7.59 1100 0.6056 0.5000
0.5007 8.28 1200 0.5870 0.4918
0.3854 8.97 1300 0.6200 0.4804
0.264 9.66 1400 0.6030 0.4600
0.1989 10.34 1500 0.6049 0.4588
0.3196 11.03 1600 0.5946 0.4599
0.2622 11.72 1700 0.6282 0.4422
0.1697 12.41 1800 0.6559 0.4413
0.1464 13.1 1900 0.6349 0.4328
0.2277 13.79 2000 0.6133 0.4284
0.221 14.48 2100 0.6617 0.4219
0.1391 15.17 2200 0.6705 0.4235
0.112 15.86 2300 0.6207 0.4218
0.1717 16.55 2400 0.6749 0.4184
0.2081 17.24 2500 0.6756 0.4169
0.1244 17.93 2600 0.6750 0.4181
0.0978 18.62 2700 0.6500 0.4115
0.128 19.31 2800 0.6750 0.4106
0.1791 20.0 2900 0.6712 0.4101

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/unispeech-sat-base-timit-ft