automatic-speech-recognition /workspace/datasets/datasets/MIR_ST500/MIR_ST500.py generated_from_trainer

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

wav2vec2-base-MIR_ST500_ASR_109

This model is a fine-tuned version of facebook/wav2vec2-base on the /WORKSPACE/DATASETS/DATASETS/MIR_ST500/MIR_ST500.PY - ASR 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
12.5751 0.27 100 6.0291 1.0
4.343 0.53 200 2.8709 1.0
4.1911 0.8 300 2.5472 1.0
2.4535 1.06 400 2.4323 1.0
2.6157 1.33 500 2.2799 1.0
2.4839 1.6 600 2.2722 1.0
2.2787 1.86 700 2.2269 1.0
2.1981 2.13 800 2.2221 1.0
2.159 2.39 900 2.1657 1.0
2.1421 2.66 1000 2.1769 1.0
2.0841 2.93 1100 2.1688 1.0
2.0599 3.19 1200 2.1141 1.0
2.0257 3.46 1300 2.0445 1.0
1.979 3.72 1400 2.0180 1.0
1.9366 3.99 1500 1.9419 1.0
1.8547 4.26 1600 1.8765 1.0
1.3988 4.52 1700 1.4151 0.7999
1.1881 4.79 1800 1.1158 0.7347
0.9557 5.05 1900 1.0095 0.6485
0.9087 5.32 2000 0.9644 0.6848
0.8086 5.59 2100 0.8960 0.6119
0.9106 5.85 2200 0.8892 0.5941
0.8252 6.12 2300 0.8333 0.5756
0.8299 6.38 2400 0.8559 0.5838
0.8021 6.65 2500 0.8201 0.5883
0.7979 6.91 2600 0.8349 0.575
0.7223 7.18 2700 0.7883 0.5563
0.6754 7.45 2800 0.7590 0.5393
0.6454 7.71 2900 0.7411 0.5291
0.6228 7.98 3000 0.7464 0.5300
0.6475 8.24 3100 0.7478 0.5295
0.6452 8.51 3200 0.7555 0.5360
0.5636 8.78 3300 0.7369 0.5232
0.564 9.04 3400 0.7331 0.5076
0.6173 9.31 3500 0.7199 0.5034
0.625 9.57 3600 0.7243 0.5193
0.8122 9.84 3700 0.7436 0.5242
0.5455 10.11 3800 0.7111 0.4920
0.7928 10.37 3900 0.7137 0.4858
0.5446 10.64 4000 0.6874 0.4828
0.4772 10.9 4100 0.6760 0.4801
0.6447 11.17 4200 0.6893 0.4886
0.5818 11.44 4300 0.6789 0.4740
0.4952 11.7 4400 0.7043 0.4811
0.5722 11.97 4500 0.6794 0.4766
0.58 12.23 4600 0.6629 0.4580
0.5432 12.5 4700 0.6907 0.4906
0.4786 12.77 4800 0.6925 0.4854
0.5177 13.03 4900 0.6666 0.4532
0.5448 13.3 5000 0.6744 0.4542
0.5732 13.56 5100 0.6930 0.4986
0.5065 13.83 5200 0.6647 0.4351
0.4005 14.1 5300 0.6659 0.4508
0.4256 14.36 5400 0.6682 0.4533
0.4459 14.63 5500 0.6594 0.4326
0.4645 14.89 5600 0.6615 0.4287
0.4275 15.16 5700 0.6423 0.4299
0.4026 15.43 5800 0.6539 0.4217
0.3507 15.69 5900 0.6555 0.4299
0.3998 15.96 6000 0.6526 0.4213
0.4462 16.22 6100 0.6469 0.4230
0.4095 16.49 6200 0.6516 0.4210
0.4452 16.76 6300 0.6373 0.4133
0.3997 17.02 6400 0.6456 0.4211
0.3826 17.29 6500 0.6278 0.4042
0.3867 17.55 6600 0.6459 0.4112
0.4367 17.82 6700 0.6464 0.4131
0.3887 18.09 6800 0.6567 0.4150
0.3481 18.35 6900 0.6548 0.4145
0.4241 18.62 7000 0.6490 0.4123
0.3742 18.88 7100 0.6561 0.4135
0.423 19.15 7200 0.6498 0.4051
0.3803 19.41 7300 0.6475 0.3903
0.3084 19.68 7400 0.6403 0.4042
0.3012 19.95 7500 0.6460 0.4004
0.3306 20.21 7600 0.6491 0.3837
0.3612 20.48 7700 0.6752 0.3884
0.3572 20.74 7800 0.6383 0.3793
0.3638 21.01 7900 0.6349 0.3838
0.3658 21.28 8000 0.6544 0.3793
0.3726 21.54 8100 0.6567 0.3756
0.3618 21.81 8200 0.6390 0.3795
0.3212 22.07 8300 0.6359 0.3768
0.3561 22.34 8400 0.6452 0.3732
0.3231 22.61 8500 0.6416 0.3731
0.3764 22.87 8600 0.6428 0.3697
0.4142 23.14 8700 0.6415 0.3665
0.2713 23.4 8800 0.6541 0.3676
0.2277 23.67 8900 0.6492 0.3684
0.3849 23.94 9000 0.6448 0.3651
0.266 24.2 9100 0.6602 0.3643
0.3464 24.47 9200 0.6673 0.3607
0.2919 24.73 9300 0.6557 0.3677
0.2878 25.0 9400 0.6377 0.3653
0.1603 25.27 9500 0.6598 0.3700
0.2055 25.53 9600 0.6558 0.3614
0.1508 25.8 9700 0.6543 0.3605
0.3162 26.06 9800 0.6570 0.3576
0.2613 26.33 9900 0.6604 0.3584
0.2244 26.6 10000 0.6618 0.3634
0.1585 26.86 10100 0.6698 0.3634
0.2959 27.13 10200 0.6709 0.3593
0.2778 27.39 10300 0.6638 0.3537
0.2354 27.66 10400 0.6770 0.3585
0.2992 27.93 10500 0.6698 0.3506
0.2664 28.19 10600 0.6725 0.3533
0.2582 28.46 10700 0.6689 0.3542
0.2096 28.72 10800 0.6731 0.3527
0.4169 28.99 10900 0.6691 0.3521
0.2716 29.26 11000 0.6712 0.3517
0.2944 29.52 11100 0.6708 0.3509
0.2737 29.79 11200 0.6699 0.3491

Framework versions