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wav2vec2-bert

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the Yogera dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5797
  • Wer: 0.2828
  • Cer: 0.0600

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.9705 1.0 20 2.7517 0.9999 0.8635
1.6229 2.0 40 0.7456 0.7959 0.1852
0.5343 3.0 60 0.4631 0.5219 0.1081
0.3188 4.0 80 0.3815 0.3815 0.0788
0.2219 5.0 100 0.3961 0.3946 0.0786
0.18 6.0 120 0.3851 0.3340 0.0698
0.1388 7.0 140 0.4074 0.3508 0.0723
0.1262 8.0 160 0.3911 0.3110 0.0665
0.0883 9.0 180 0.4100 0.3058 0.0636
0.0681 10.0 200 0.4071 0.3096 0.0644
0.0553 11.0 220 0.4505 0.3132 0.0662
0.0546 12.0 240 0.4836 0.3156 0.0681
0.038 13.0 260 0.4465 0.2941 0.0631
0.0374 14.0 280 0.5048 0.3071 0.0645
0.0275 15.0 300 0.4964 0.2901 0.0600
0.0207 16.0 320 0.4497 0.2946 0.0611
0.0163 17.0 340 0.4992 0.2867 0.0599
0.0248 18.0 360 0.5160 0.2952 0.0626
0.0139 19.0 380 0.5196 0.2960 0.0612
0.0177 20.0 400 0.5026 0.2933 0.0608
0.013 21.0 420 0.5212 0.2852 0.0603
0.0103 22.0 440 0.5277 0.2847 0.0599
0.01 23.0 460 0.5850 0.2802 0.0597
0.0088 24.0 480 0.5362 0.2841 0.0584
0.0074 25.0 500 0.5401 0.2974 0.0612
0.0087 26.0 520 0.5586 0.2858 0.0593
0.0077 27.0 540 0.5924 0.2859 0.0614
0.0114 28.0 560 0.5722 0.2828 0.0599
0.0118 29.0 580 0.5475 0.2842 0.0579
0.0102 30.0 600 0.5249 0.2851 0.0584
0.0083 31.0 620 0.5724 0.2801 0.0584
0.0087 32.0 640 0.5742 0.2799 0.0596
0.0098 33.0 660 0.5797 0.2828 0.0600

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.1.0+cu118
  • Datasets 3.0.1
  • Tokenizers 0.20.1
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Evaluation results