CoolFace
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NbAiLab/wav2vec2-1b-npsc-nst-bokmaal-repaired

sourceHugging Faceapache-2.0updated 6mo agoView on Hugging Face
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Model Card

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wav2vec2-1b-npsc-nst-bokmaal-repaired

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0666
  • —Wer: 0.0349

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: 2e-05
  • —trainbatchsize: 12
  • —evalbatchsize: 12
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 24
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 2000
  • —num_epochs: 40.0
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
2.91990.045002.76951.0
0.75290.0810000.62340.6100
0.5410.1215000.40890.3949
0.52740.1620000.23230.2240
0.44340.225000.19540.1917
0.41110.2430000.17810.1677
0.4030.2835000.15090.1466
0.37250.3240000.14330.1369
0.38680.3645000.14360.1279
0.30780.3950000.13590.1316
0.27420.4355000.13010.1241
0.26950.4760000.12460.1173
0.24770.5165000.11770.1129
0.24580.5570000.11990.1125
0.24690.5975000.11280.1103
0.23130.6380000.10720.1050
0.2420.6785000.10960.1055
0.2470.7190000.10130.1018
0.20930.7595000.10520.1009
0.20480.79100000.10360.1002
0.23080.83105000.10480.0987
0.19790.87110000.10070.0945
0.19440.91115000.10090.0967
0.21470.95120000.09540.0924
0.20530.99125000.09720.1032
0.17231.03130000.09500.0908
0.16791.07135000.09230.0871
0.18391.11140000.09240.0879
0.18221.14145000.09020.0874
0.17741.18150000.08940.0859
0.19241.22155000.08590.0829
0.16681.26160000.08550.0829
0.17331.3165000.08410.0810
0.18131.34170000.08380.0808
0.17641.38175000.08400.0812
0.19231.42180000.08250.0815
0.16641.46185000.08180.0823
0.1711.5190000.08140.0802
0.16031.54195000.08120.0804
0.16911.58200000.07840.0790
0.16111.62205000.08100.0790
0.15831.66210000.08180.0780
0.16441.7215000.07770.0785
0.16191.74220000.07810.0775
0.17011.78225000.07400.0792
0.16721.82230000.07750.0772
0.16521.86235000.07770.0771
0.15261.89240000.07820.0781
0.15291.93245000.07510.0758
0.16451.97250000.07460.0764
0.13892.01255000.07510.0753
0.1462.05260000.07350.0740
0.15282.09265000.07430.0731
0.14832.13270000.07870.0751
0.13932.17275000.07600.0735
0.14272.21280000.07650.0747
0.13992.25285000.07270.0727
0.15462.29290000.07160.0731
0.14272.33295000.07200.0717
0.14022.37300000.07230.0716
0.13892.41305000.07350.0723
0.13222.45310000.07130.0708
0.13942.49315000.07120.0708
0.13952.53320000.07110.0734
0.13162.57325000.06930.0693
0.13022.61330000.06950.0700
0.13442.64335000.07020.0700
0.13422.68340000.07030.0699
0.12312.72345000.07060.0707
0.1262.76350000.06980.0703
0.13112.8355000.06890.0698
0.13792.84360000.07010.0697
0.12712.88365000.06950.0693
0.1322.92370000.06890.0705
0.13292.96375000.06860.0688
0.12933.0380000.06750.0689
0.14353.04385000.06720.0685
0.11663.08390000.07120.0706
0.12263.12395000.06690.0691
0.11733.16400000.06670.0668
0.11983.2405000.06750.0675
0.11233.24410000.06910.0685
0.11453.28415000.06820.0692
0.12263.32420000.06670.0678
0.11963.36425000.06590.0667
0.11673.39430000.07150.0672
0.12263.43435000.06630.0653
0.23983.47440000.06540.0656
0.12173.51445000.06690.0670
0.13013.55450000.06330.0659
0.11363.59455000.06580.0664
0.12443.63460000.06560.0648
0.13013.67465000.06520.0652
0.11323.71470000.06440.0645
0.12113.75475000.06560.0663
0.11923.79480000.06760.0652
0.12753.83485000.06440.0663
0.11173.87490000.06200.0650
0.11293.91495000.06290.0649
0.10443.95500000.06570.0642
0.12563.99505000.06170.0631
0.11634.03510000.06440.0643
0.10174.07515000.06350.0630
0.11144.11520000.06500.0639
0.12824.14525000.06310.0629
0.11594.18530000.06240.0624
0.10964.22535000.06420.0628
0.11824.26540000.06350.0630
0.10274.3545000.06240.0623
0.10674.34550000.06430.0622
0.10764.38555000.06240.0634
0.11054.42560000.06090.0625
0.1014.46565000.06250.0626
0.11274.5570000.06120.0618
0.11414.54575000.06110.0619
0.10694.58580000.06000.0623
0.22664.62585000.06120.0607
0.10254.66590000.06030.0604
0.10364.7595000.06200.0624
0.11134.74600000.06040.0599
0.10934.78605000.06090.0601
0.11424.82610000.06080.0598
0.11094.86615000.06030.0602
0.09854.89620000.06280.0606
0.10564.93625000.06190.0597
0.10544.97630000.05900.0581
0.08885.01635000.05710.0593
0.09595.05640000.05920.0596
0.09515.09645000.05970.0593
0.10645.13650000.06250.0591
0.10795.17655000.05960.0587
0.09465.21660000.05870.0588
0.09645.25665000.06130.0597
0.09645.29670000.05910.0581
0.10165.33675000.05780.0578
0.10515.37680000.05720.0581
0.10085.41685000.05990.0586
0.10415.45690000.06070.0576
0.10115.49695000.05870.0579
0.09945.53700000.05650.0584
0.15.57705000.05900.0575
0.09315.61710000.06080.0580
0.1045.64715000.05760.0578
0.10995.68720000.05860.0589
0.09945.72725000.05910.0577
0.10115.76730000.06010.0591
0.10985.8735000.05610.0594
0.08895.84740000.05840.0582
0.10975.88745000.05730.0577
0.10755.92750000.05790.0586
0.09475.96755000.05730.0571
0.0986.0760000.05790.0566
0.08116.04765000.05850.0585
0.0836.08770000.06080.0588
0.096.12775000.06240.0571
0.09296.16780000.06310.0582
0.09086.2785000.05960.0597
0.09096.24790000.05640.0571
0.08776.28795000.05730.0624
0.09026.32800000.06020.0577
0.08986.36805000.05690.0560
0.09166.39810000.05830.0577
0.09456.43815000.05580.0573
0.08566.47820000.05740.0568
0.10246.51825000.06120.0573
0.08816.55830000.05740.0571
0.16.59835000.05620.0564
0.09456.63840000.05800.0561
0.09076.67845000.05700.0556
0.09426.71850000.05690.0573
0.09596.75855000.05560.0571
0.09726.79860000.05780.0552
0.08546.83865000.05690.0567
0.08196.87870000.05720.0550
0.09286.91875000.05670.0559
0.09126.95880000.05400.0543
0.09286.99885000.05740.0542
0.08767.03890000.05490.0540
0.08097.07895000.05650.0546
0.08347.11900000.05650.0560
0.08657.14905000.05620.0555
0.08257.18910000.05690.0562
0.08277.22915000.05770.0541
0.08617.26920000.05730.0551
0.09257.3925000.05600.0540
0.08087.34930000.05640.0534
0.09487.38935000.05520.0530
0.0917.42940000.05570.0539
0.07517.46945000.05820.0531
0.09967.5950000.05660.0541
0.09667.54955000.05580.0547
0.08457.58960000.05510.0551
0.08277.62965000.05590.0536
0.0837.66970000.05550.0536
0.07537.7975000.05560.0540
0.09187.74980000.05540.0530
0.0897.78985000.05570.0530
0.0817.82990000.05360.0526
0.07757.86995000.05540.0535
0.08457.891000000.05350.0538
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0.07948.171035000.05370.0530
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0.07788.641095000.05430.0523
0.08178.681100000.05520.0521
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0.08348.761110000.05180.0527
0.07398.81115000.05430.0520
0.08188.841120000.05370.0517
0.07098.881125000.05410.0516
0.07658.921130000.05320.0512
0.07578.961135000.05150.0520
0.07539.01140000.05310.0512
0.07279.041145000.05320.0514
0.06949.081150000.05570.0525
0.07739.121155000.05270.0542
0.07089.161160000.05630.0515
0.07069.21165000.05350.0509
0.07569.241170000.05510.0504
0.07889.281175000.05330.0515
0.07259.321180000.05110.0500
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0.07479.431195000.05380.0515
0.07649.471200000.05450.0515
0.06959.511205000.05420.0511
0.06889.551210000.05470.0507
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0.06699.631220000.05300.0517
0.06829.671225000.05410.0509
0.07619.711230000.05540.0518
0.07829.751235000.05290.0511
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0.07979.911255000.05550.0500
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0.069210.031270000.05410.0499
0.068310.071275000.05440.0505
0.064410.11280000.05260.0500
0.061610.141285000.05240.0498
0.065810.181290000.05400.0500
0.070810.221295000.05170.0505
0.065610.261300000.05390.0502
0.066610.31305000.05440.0509
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0.066510.381315000.05300.0505
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Framework versions

  • —Transformers 4.18.0
  • —Pytorch 1.11.0+cu113
  • —Datasets 2.1.0
  • —Tokenizers 0.12.1