generated_from_keras_callback

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whisper_char_cv12_pad_lob100_low__0050

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
0.3330 0.0999 1.7359 0.3779 0.0615 4.7471 0
0.3093 0.1007 2.0563 0.3652 0.0618 7.2181 1
0.2869 0.1015 2.0654 0.3539 0.0620 8.6857 2
0.2672 0.1022 2.1925 0.3443 0.0623 8.0906 3
0.2488 0.1028 2.3286 0.3305 0.0626 9.1756 4
0.2316 0.1034 2.4212 0.3300 0.0626 8.1427 5
0.2163 0.1039 2.5012 0.3183 0.0629 8.3043 6
0.2018 0.1045 2.7267 0.3109 0.0631 9.5329 7
0.1878 0.1050 2.7034 0.3053 0.0632 7.9014 8
0.1749 0.1054 2.8719 0.3063 0.0632 9.0257 9
0.1628 0.1058 2.8764 0.3033 0.0634 9.1336 10
0.1510 0.1063 2.8441 0.3046 0.0634 8.6064 11
0.1391 0.1067 2.9377 0.3030 0.0635 9.1326 12
0.1280 0.1071 2.9433 0.3025 0.0636 9.4533 13
0.1182 0.1075 3.1399 0.3076 0.0636 9.9836 14
0.1086 0.1078 3.2411 0.3096 0.0636 8.8470 15
0.0983 0.1082 3.2622 0.3125 0.0636 9.1506 16
0.0889 0.1086 3.3368 0.3184 0.0636 8.9635 17
0.0803 0.1089 3.2742 0.3204 0.0637 9.3550 18
0.0720 0.1092 3.4052 0.3258 0.0637 10.1082 19
0.0637 0.1096 3.4287 0.3342 0.0637 10.3977 20
0.0566 0.1098 3.4708 0.3411 0.0636 10.6479 21
0.0498 0.1101 3.4462 0.3463 0.0637 10.1602 22
0.0429 0.1104 3.4056 0.3588 0.0636 9.7172 23
0.0374 0.1106 3.4477 0.3656 0.0636 9.4476 24
0.0325 0.1108 3.4474 0.3712 0.0637 9.6926 25
0.0279 0.1109 3.4263 0.3836 0.0636 10.0768 26
0.0233 0.1111 3.4779 0.3873 0.0637 9.8123 27
0.0196 0.1112 3.5329 0.4015 0.0636 10.0477 28
0.0160 0.1113 3.5049 0.4097 0.0636 10.4027 29
0.0139 0.1114 3.6185 0.4201 0.0636 10.9904 30
0.0112 0.1114 3.5812 0.4300 0.0636 10.4501 31
0.0096 0.1115 3.7493 0.4409 0.0636 10.3964 32
0.0089 0.1115 3.6912 0.4499 0.0636 10.8345 33
0.0082 0.1115 3.7577 0.4583 0.0636 10.2883 34
0.0090 0.1114 3.8468 0.4755 0.0635 11.8086 35
0.0168 0.1111 3.6340 0.4592 0.0636 10.6373 36
0.0072 0.1115 3.8163 0.4644 0.0637 10.2448 37
0.0040 0.1115 3.8376 0.4728 0.0637 10.9074 38
0.0029 0.1115 3.8274 0.4814 0.0637 10.5440 39
0.0025 0.1115 3.8022 0.4891 0.0637 10.8606 40
0.0021 0.1115 3.8940 0.4937 0.0637 10.9388 41
0.0018 0.1115 3.8026 0.5030 0.0637 10.6511 42
0.0014 0.1115 3.8260 0.5092 0.0637 10.5743 43
0.0173 0.1110 3.6223 0.5066 0.0635 9.9370 44
0.0073 0.1114 3.6868 0.4972 0.0637 10.6775 45
0.0027 0.1115 3.6742 0.5025 0.0638 10.3476 46
0.0016 0.1115 3.7677 0.5078 0.0638 10.2277 47
0.0013 0.1115 3.7721 0.5131 0.0638 10.4473 48
0.0011 0.1115 3.8394 0.5189 0.0638 10.4344 49

Framework versions