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

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wav2vec2-large-xlsr-53-MIR_ST500_ASR

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 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
56.764 0.13 100 24.4254 0.9990
7.5081 0.27 200 2.9111 1.0
3.4899 0.4 300 2.1361 1.0
2.4094 0.53 400 1.9088 1.0
2.6764 0.67 500 1.8543 1.0
3.3107 0.8 600 1.7979 1.0
2.2856 0.93 700 1.7571 1.0
1.856 1.07 800 1.7351 0.9648
1.8882 1.2 900 1.7181 0.9654
2.1731 1.33 1000 1.6736 0.9637
1.8252 1.46 1100 1.3468 0.9647
1.9092 1.6 1200 1.3302 0.9627
1.9435 1.73 1300 1.2428 0.9634
1.3027 1.86 1400 1.2133 0.9644
1.3438 2.0 1500 1.2002 0.9635
1.2161 2.13 1600 1.1901 0.9636
1.203 2.26 1700 1.1620 0.9616
1.1159 2.4 1800 1.1660 0.9598
1.1466 2.53 1900 1.2089 0.9605
1.0563 2.66 2000 1.1732 0.9603
1.1019 2.8 2100 1.1468 0.9612
1.029 2.93 2200 1.1188 0.9622
1.0079 3.06 2300 1.0604 0.9617
1.0483 3.2 2400 1.0499 0.9612
0.9892 3.33 2500 1.0292 0.9606
0.9556 3.46 2600 1.0228 0.9604
0.9626 3.6 2700 1.0028 0.9617
1.0537 3.73 2800 1.0051 0.9608
1.0648 3.86 2900 0.9723 0.9604
0.8657 3.99 3000 0.9620 0.9605
0.8964 4.13 3100 1.0432 0.9612
0.9639 4.26 3200 0.9322 0.9589
0.8965 4.39 3300 0.9091 0.9559
0.8257 4.53 3400 0.8999 0.9499
0.8002 4.66 3500 0.8754 0.9554
0.7335 4.79 3600 0.8608 0.9572
0.936 4.93 3700 0.8564 0.9510
0.8185 5.06 3800 0.8890 0.9517
0.7422 5.19 3900 0.8262 0.9392
0.7784 5.33 4000 0.8292 0.9259
0.8123 5.46 4100 0.8180 0.9374
0.7256 5.59 4200 0.8158 0.9077
0.7638 5.73 4300 0.8423 0.9170
0.6737 5.86 4400 0.7818 0.9182
0.7644 5.99 4500 0.7692 0.8934
0.7911 6.13 4600 0.7627 0.8978
0.6922 6.26 4700 0.7627 0.8906
0.7369 6.39 4800 0.7570 0.8838
0.6642 6.52 4900 0.9476 0.8953
0.7502 6.66 5000 0.7336 0.8955
0.6243 6.79 5100 0.7583 0.8896
0.6912 6.92 5200 0.7764 0.8761
0.7744 7.06 5300 0.7615 0.8790
0.6195 7.19 5400 0.7114 0.8712
0.7418 7.32 5500 0.8314 0.8864
0.7658 7.46 5600 0.8531 0.8718
0.6821 7.59 5700 0.9068 0.8786
0.6931 7.72 5800 0.7549 0.8645
0.6771 7.86 5900 0.7138 0.8442
0.6735 7.99 6000 0.6947 0.8493
0.6427 8.12 6100 0.6997 0.8475
0.6988 8.26 6200 0.6814 0.8098
0.6726 8.39 6300 0.6656 0.8259
0.6247 8.52 6400 0.6438 0.8314
0.5101 8.66 6500 0.6323 0.8446
0.5325 8.79 6600 0.6305 0.8413
0.5918 8.92 6700 0.6353 0.8076
0.617 9.05 6800 0.6544 0.8118
0.4861 9.19 6900 0.6174 0.8429
0.6396 9.32 7000 0.6140 0.8117
0.436 9.45 7100 0.6148 0.7887
0.6141 9.59 7200 0.6133 0.8007
0.5781 9.72 7300 0.6135 0.8211
0.52 9.85 7400 0.6155 0.8042
0.6681 9.99 7500 0.6074 0.7843
0.5004 10.12 7600 0.5950 0.8035
0.4993 10.25 7700 0.5888 0.7710
0.4768 10.39 7800 0.5922 0.7633
0.4535 10.52 7900 0.5906 0.8030
0.517 10.65 8000 0.5875 0.7823
0.5894 10.79 8100 0.5882 0.7932
0.6005 10.92 8200 0.5798 0.7922
0.4284 11.05 8300 0.5775 0.7701
0.5163 11.19 8400 0.5715 0.7592
0.4701 11.32 8500 0.5955 0.7485
0.5152 11.45 8600 0.6041 0.6914
0.4442 11.58 8700 0.5614 0.7439
0.4451 11.72 8800 0.5619 0.7033
0.4433 11.85 8900 0.5562 0.7246
0.4799 11.98 9000 0.5834 0.7040
0.4832 12.12 9100 0.5902 0.7349
0.523 12.25 9200 0.5562 0.7326
0.4419 12.38 9300 0.5472 0.7326
0.437 12.52 9400 0.5466 0.7100
0.4797 12.65 9500 0.5470 0.6698
0.3971 12.78 9600 0.5437 0.6835
0.5254 12.92 9700 0.5385 0.6747
0.5046 13.05 9800 0.5330 0.6554
0.4692 13.18 9900 0.5305 0.6527
0.4305 13.32 10000 0.5292 0.6314
0.6132 13.45 10100 0.5405 0.6028
0.4741 13.58 10200 0.5311 0.6207
0.398 13.72 10300 0.5320 0.6261
0.458 13.85 10400 0.5240 0.6242
0.4154 13.98 10500 0.5262 0.6215
0.3702 14.11 10600 0.5206 0.6136
0.427 14.25 10700 0.5231 0.6289
0.4307 14.38 10800 0.5210 0.5908
0.4738 14.51 10900 0.5211 0.5826
0.5522 14.65 11000 0.5193 0.5886
0.4717 14.78 11100 0.5194 0.5907
0.4819 14.91 11200 0.5178 0.5870

Framework versions