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unispeech-sat-large-timit-ft

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

  • Loss: 0.6074
  • Wer: 0.3880

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
6.2516 0.69 100 5.8638 1.0
2.9596 1.38 200 2.9550 1.0
2.8831 2.07 300 2.8547 1.0
2.3223 2.76 400 2.2044 1.0063
1.2104 3.45 500 1.0845 0.7706
0.6779 4.14 600 0.7342 0.5663
0.6319 4.83 700 0.6054 0.4881
0.664 5.52 800 0.5808 0.4913
0.402 6.21 900 0.5647 0.4611
0.3176 6.9 1000 0.5211 0.4440
0.3392 7.59 1100 0.5187 0.4359
0.3888 8.28 1200 0.5501 0.4391
0.2874 8.97 1300 0.5249 0.4148
0.208 9.66 1400 0.5407 0.4152
0.1457 10.34 1500 0.5722 0.4155
0.2375 11.03 1600 0.5780 0.4059
0.2111 11.72 1700 0.5823 0.4094
0.1422 12.41 1800 0.5754 0.3977
0.125 13.1 1900 0.5784 0.4031
0.1996 13.79 2000 0.5630 0.3956
0.1747 14.48 2100 0.5880 0.3964
0.1263 15.17 2200 0.5987 0.3951
0.11 15.86 2300 0.5688 0.3964
0.1411 16.55 2400 0.6223 0.3906
0.1647 17.24 2500 0.6135 0.3960
0.1162 17.93 2600 0.6224 0.3960
0.098 18.62 2700 0.6017 0.3907
0.1183 19.31 2800 0.6121 0.3885
0.1717 20.0 2900 0.6074 0.3880

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-large-timit-ft