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unispeech-large-1500h-cv-timit

This model is a fine-tuned version of microsoft/unispeech-large-1500h-cv on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3099
  • Wer: 0.2196

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
4.64 0.69 100 3.9717 0.9981
2.6793 1.38 200 2.6264 1.0
1.2221 2.07 300 0.9999 0.7167
0.9009 2.76 400 0.6509 0.5570
0.4352 3.45 500 0.4682 0.4332
0.227 4.14 600 0.3661 0.3565
0.2169 4.83 700 0.3244 0.3203
0.2687 5.52 800 0.3137 0.2981
0.127 6.21 900 0.3220 0.2828
0.0922 6.9 1000 0.3075 0.2708
0.0965 7.59 1100 0.2779 0.2576
0.1298 8.28 1200 0.3111 0.2480
0.0855 8.97 1300 0.3021 0.2421
0.0629 9.66 1400 0.3122 0.2511
0.0471 10.34 1500 0.2965 0.2368
0.0871 11.03 1600 0.3247 0.2387
0.0503 11.72 1700 0.3359 0.2363
0.0402 12.41 1800 0.2976 0.2332
0.0336 13.1 1900 0.3139 0.2321
0.0634 13.79 2000 0.3188 0.2309
0.0429 14.48 2100 0.3145 0.2335
0.028 15.17 2200 0.3244 0.2242
0.0255 15.86 2300 0.2914 0.2196
0.0406 16.55 2400 0.3249 0.2202
0.0512 17.24 2500 0.3037 0.2198
0.0269 17.93 2600 0.3218 0.2242
0.0287 18.62 2700 0.3106 0.2185
0.0319 19.31 2800 0.3124 0.2217
0.0494 20.0 2900 0.3099 0.2196

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-large-1500h-cv-timit