wav2vec2-base-repro-timit

This model is a fine-tuned version of patrickvonplaten/wav2vec2-base-repro-960h-libri-85k-steps on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8562
  • Wer: 0.5484

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
5.9793 0.69 100 5.4532 1.0
2.9066 1.38 200 2.9070 1.0
2.2562 2.07 300 2.0323 1.0
1.5273 2.76 400 1.1510 0.8001
1.1085 3.45 500 0.9521 0.7053
0.813 4.14 600 0.8617 0.6702
0.8434 4.83 700 0.8068 0.6393
0.9631 5.52 800 0.7863 0.6248
0.707 6.21 900 0.7476 0.5973
0.5568 6.9 1000 0.7350 0.5911
0.6171 7.59 1100 0.7171 0.5841
0.7011 8.28 1200 0.7318 0.5798
0.5546 8.97 1300 0.7447 0.5767
0.4278 9.66 1400 0.7481 0.5650
0.3576 10.34 1500 0.7443 0.5713
0.5506 11.03 1600 0.7574 0.5664
0.4127 11.72 1700 0.8043 0.5631
0.3251 12.41 1800 0.7738 0.5550
0.3119 13.1 1900 0.7829 0.5516
0.4371 13.79 2000 0.8025 0.5556
0.3772 14.48 2100 0.8451 0.5559
0.2942 15.17 2200 0.8300 0.5556
0.2503 15.86 2300 0.8417 0.5541
0.3671 16.55 2400 0.8568 0.5528
0.3867 17.24 2500 0.8521 0.5510
0.2614 17.93 2600 0.8479 0.5523
0.2441 18.62 2700 0.8558 0.5494
0.3059 19.31 2800 0.8553 0.5474
0.3734 20.0 2900 0.8562 0.5484

Framework versions

  • Transformers 4.12.0.dev0
  • Pytorch 1.8.1
  • Datasets 1.14.1.dev0
  • Tokenizers 0.10.3
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