generated_from_trainer

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wav2vec2-large-multilang-cv-ru-night

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Wer
8.725 1.58 500 3.2788 1.0
3.1184 3.15 1000 2.4018 1.0015
1.2393 4.73 1500 0.6213 0.7655
0.6899 6.31 2000 0.5518 0.6811
0.5532 7.89 2500 0.5102 0.6467
0.4604 9.46 3000 0.4887 0.6213
0.4095 11.04 3500 0.4874 0.6042
0.3565 12.62 4000 0.4810 0.5893
0.3238 14.2 4500 0.5028 0.5890
0.3011 15.77 5000 0.5475 0.5808
0.2827 17.35 5500 0.5289 0.5720
0.2659 18.93 6000 0.5496 0.5733
0.2445 20.5 6500 0.5354 0.5737
0.2366 22.08 7000 0.5357 0.5686
0.2181 23.66 7500 0.5491 0.5611
0.2146 25.24 8000 0.5591 0.5597
0.2006 26.81 8500 0.5625 0.5631
0.1912 28.39 9000 0.5577 0.5647
0.1821 29.97 9500 0.5684 0.5519
0.1744 31.55 10000 0.5639 0.5551
0.1691 33.12 10500 0.5596 0.5425
0.1577 34.7 11000 0.5770 0.5551
0.1522 36.28 11500 0.5634 0.5560
0.1468 37.85 12000 0.5815 0.5453
0.1508 39.43 12500 0.6053 0.5490
0.1394 41.01 13000 0.6193 0.5504
0.1291 42.59 13500 0.5930 0.5424
0.1345 44.16 14000 0.6283 0.5442
0.1296 45.74 14500 0.6063 0.5560
0.1286 47.32 15000 0.6248 0.5378
0.1231 48.9 15500 0.6106 0.5405
0.1189 50.47 16000 0.6164 0.5342
0.1127 52.05 16500 0.6269 0.5359
0.112 53.63 17000 0.6170 0.5390
0.1113 55.21 17500 0.6489 0.5385
0.1023 56.78 18000 0.6826 0.5490
0.1069 58.36 18500 0.6147 0.5296
0.1008 59.94 19000 0.6414 0.5332
0.1018 61.51 19500 0.6454 0.5288
0.0989 63.09 20000 0.6603 0.5303
0.0944 64.67 20500 0.6350 0.5288
0.0905 66.25 21000 0.6386 0.5247
0.0837 67.82 21500 0.6563 0.5298
0.0868 69.4 22000 0.6375 0.5208
0.0827 70.98 22500 0.6401 0.5271
0.0797 72.56 23000 0.6723 0.5191
0.0847 74.13 23500 0.6610 0.5213
0.0818 75.71 24000 0.6774 0.5254
0.0793 77.29 24500 0.6543 0.5250
0.0758 78.86 25000 0.6607 0.5218
0.0755 80.44 25500 0.6599 0.5160
0.0722 82.02 26000 0.6683 0.5196
0.0714 83.6 26500 0.6941 0.5180
0.0684 85.17 27000 0.6581 0.5167
0.0686 86.75 27500 0.6651 0.5172
0.0712 88.33 28000 0.6547 0.5208
0.0697 89.91 28500 0.6555 0.5162
0.0696 91.48 29000 0.6678 0.5107
0.0686 93.06 29500 0.6630 0.5124
0.0671 94.64 30000 0.6675 0.5143
0.0668 96.21 30500 0.6602 0.5107
0.0666 97.79 31000 0.6611 0.5097
0.0664 99.37 31500 0.6617 0.5097

Framework versions