generated_from_keras_callback

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whisper_char_cv12_pad_lob100_low_sup__0085

This model is a fine-tuned version of openai/whisper-tiny on an unknown 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

Train Loss Train Accuracy Train Wermet Validation Loss Validation Accuracy Validation Wermet Epoch
2.5942 0.0399 3.6402 1.9371 0.0319 16.1531 0
1.8766 0.0532 6.8384 1.7437 0.0343 15.0408 1
1.7251 0.0570 5.9150 1.6630 0.0358 10.5002 2
1.6457 0.0591 5.1153 1.5993 0.0369 10.4737 3
1.5935 0.0604 4.8231 1.5582 0.0375 8.5794 4
1.5526 0.0615 4.1987 1.5103 0.0385 9.4130 5
1.5165 0.0625 4.0179 1.4812 0.0391 6.6025 6
1.4868 0.0633 3.6770 1.4465 0.0399 6.7562 7
1.4565 0.0642 3.3851 1.4326 0.0402 6.3327 8
1.4271 0.0650 3.2883 1.3788 0.0413 6.5933 9
1.3965 0.0659 3.0822 1.3558 0.0415 5.7852 10
1.3541 0.0671 2.8659 1.2958 0.0429 5.2978 11
1.3066 0.0684 2.4942 1.2323 0.0440 4.9600 12
1.2401 0.0703 2.0745 1.1430 0.0456 3.6837 13
1.1549 0.0728 1.6202 1.0353 0.0478 2.9217 14
1.0653 0.0755 1.3041 0.9650 0.0492 2.0673 15
0.9765 0.0783 1.0922 0.8766 0.0510 2.7441 16
0.8977 0.0808 1.2561 0.8053 0.0524 3.6015 17
0.8246 0.0831 1.2955 0.7391 0.0537 3.2922 18
0.7591 0.0852 1.3109 0.7221 0.0541 3.6946 19
0.6988 0.0872 1.3303 0.6366 0.0559 3.8377 20
0.6424 0.0891 1.3256 0.5883 0.0569 4.1079 21
0.5925 0.0908 1.3637 0.5649 0.0575 3.7297 22
0.5405 0.0925 1.3142 0.5193 0.0584 3.5121 23
0.4929 0.0942 1.3157 0.4836 0.0591 4.8017 24
0.4523 0.0956 1.4635 0.4542 0.0598 4.5538 25
0.4116 0.0971 1.5118 0.4377 0.0602 4.9221 26
0.3759 0.0984 1.6392 0.4101 0.0608 5.6152 27
0.3446 0.0994 1.7744 0.3890 0.0613 7.0303 28
0.3176 0.1004 2.1998 0.3751 0.0616 8.1772 29
0.2945 0.1012 2.5525 0.3598 0.0619 8.2165 30
0.2739 0.1019 2.7708 0.3425 0.0623 9.8904 31
0.2553 0.1026 3.0620 0.3336 0.0625 9.8263 32
0.2380 0.1032 3.3150 0.3248 0.0627 10.1323 33
0.2225 0.1037 3.4188 0.3186 0.0629 9.8005 34
0.2074 0.1043 3.4245 0.3194 0.0629 10.0836 35
0.1921 0.1048 3.5998 0.3096 0.0631 10.9020 36
0.1795 0.1053 3.7938 0.3075 0.0632 11.1284 37
0.1671 0.1057 3.7413 0.3038 0.0633 10.9362 38
0.1546 0.1061 3.7830 0.3024 0.0634 10.7771 39
0.1432 0.1066 3.6808 0.3035 0.0635 11.4689 40
0.1319 0.1070 3.7824 0.3027 0.0635 10.9949 41
0.1211 0.1074 3.9301 0.3060 0.0636 10.8937 42
0.1113 0.1077 3.8509 0.3060 0.0636 10.7188 43
0.1012 0.1081 3.8780 0.3104 0.0636 10.6993 44
0.0922 0.1085 3.6982 0.3123 0.0637 10.6308 45
0.0827 0.1088 3.7227 0.3185 0.0637 10.8392 46
0.0741 0.1092 3.7235 0.3222 0.0637 10.2774 47
0.0665 0.1095 3.7106 0.3314 0.0637 9.5736 48
0.0589 0.1098 3.6104 0.3393 0.0636 9.9114 49
0.0515 0.1100 3.6150 0.3431 0.0637 10.1000 50
0.0453 0.1103 3.6760 0.3542 0.0636 9.4499 51
0.0389 0.1105 3.7376 0.3607 0.0636 9.6629 52
0.0335 0.1107 3.7707 0.3692 0.0637 9.5104 53
0.0283 0.1109 3.7655 0.3771 0.0636 9.6379 54
0.0246 0.1110 3.9511 0.3898 0.0636 9.7582 55
0.0211 0.1111 3.9487 0.3960 0.0636 10.0651 56
0.0191 0.1112 4.0695 0.4041 0.0636 9.1873 57
0.0150 0.1113 4.2329 0.4158 0.0636 10.5777 58
0.0117 0.1114 4.3648 0.4241 0.0636 10.1904 59
0.0096 0.1115 4.3534 0.4333 0.0636 10.3831 60
0.0084 0.1115 4.4131 0.4417 0.0636 10.2134 61
0.0072 0.1115 4.4827 0.4539 0.0636 10.4537 62
0.0101 0.1114 4.6105 0.4701 0.0635 9.2620 63
0.0114 0.1113 4.4725 0.4602 0.0637 11.3443 64
0.0056 0.1115 4.6820 0.4678 0.0637 10.8401 65
0.0035 0.1115 4.7095 0.4748 0.0637 10.8410 66
0.0033 0.1115 4.5291 0.4831 0.0637 10.3950 67
0.0029 0.1115 4.4502 0.4916 0.0637 10.8216 68
0.0184 0.1110 4.2753 0.4987 0.0634 10.2126 69
0.0091 0.1113 4.1128 0.4833 0.0638 10.8605 70
0.0033 0.1115 4.1755 0.4911 0.0638 10.4538 71
0.0026 0.1115 4.3450 0.5009 0.0637 10.1961 72
0.0039 0.1115 4.6335 0.5079 0.0637 11.0165 73
0.0030 0.1115 4.5756 0.5071 0.0637 9.9384 74
0.0017 0.1115 4.6589 0.5090 0.0638 10.8814 75
0.0012 0.1115 4.8756 0.5146 0.0638 10.9099 76
0.0013 0.1115 4.9431 0.5220 0.0638 10.5558 77
0.0136 0.1111 4.8817 0.5117 0.0637 10.1668 78
0.0038 0.1115 5.1236 0.5118 0.0638 11.3651 79
0.0017 0.1115 5.3989 0.5176 0.0638 11.3609 80
0.0014 0.1115 5.5658 0.5231 0.0638 11.5637 81
0.0008 0.1115 5.4076 0.5273 0.0638 11.5293 82
0.0007 0.1116 5.5166 0.5325 0.0638 11.6874 83
0.0007 0.1115 5.3020 0.5370 0.0638 11.6410 84

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