generated_from_keras_callback

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whisper_input_decoder_no_lob_with_force__0045

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
5.4192 0.0107 1.1095 3.9799 0.0114 0.9502 0
4.7193 0.0116 0.8751 3.9335 0.0114 0.9414 1
4.6743 0.0117 0.8498 3.9949 0.0112 0.9682 2
4.6508 0.0117 0.8454 3.8900 0.0114 0.9453 3
4.6308 0.0118 0.8337 3.8853 0.0114 0.9495 4
4.6102 0.0118 0.8215 3.8884 0.0115 0.9205 5
4.5940 0.0118 0.8132 3.8409 0.0116 0.9007 6
4.5703 0.0119 0.7971 3.8224 0.0116 0.9098 7
4.5470 0.0120 0.7822 3.8013 0.0116 0.8938 8
4.5219 0.0120 0.7679 3.7776 0.0117 0.8829 9
4.4859 0.0121 0.7519 3.7360 0.0118 0.8411 10
4.4408 0.0123 0.7412 3.6972 0.0118 0.8593 11
4.3774 0.0124 0.7240 3.6035 0.0121 0.8234 12
4.2906 0.0127 0.7168 3.5057 0.0123 0.8130 13
4.1748 0.0130 0.7090 3.3528 0.0127 0.7856 14
4.0214 0.0135 0.7048 3.2086 0.0130 0.7786 15
3.8434 0.0140 0.6918 3.0436 0.0134 0.7466 16
3.6564 0.0146 0.6797 2.8693 0.0138 0.7348 17
3.4565 0.0152 0.6658 2.6967 0.0143 0.7131 18
3.2849 0.0158 0.6496 2.5221 0.0148 0.6792 19
3.0761 0.0165 0.6273 2.3796 0.0153 0.6550 20
2.9131 0.0171 0.6028 2.2468 0.0156 0.6282 21
2.7468 0.0178 0.5812 2.1322 0.0160 0.6123 22
2.6133 0.0183 0.5606 2.1131 0.0160 0.5950 23
2.4732 0.0189 0.5367 2.0006 0.0164 0.5730 24
2.3339 0.0196 0.5164 1.8895 0.0168 0.5532 25
2.2300 0.0200 0.4985 1.8183 0.0172 0.5430 26
2.1215 0.0206 0.4787 1.7413 0.0174 0.5230 27
2.0359 0.0210 0.4608 1.6732 0.0177 0.5099 28
1.9219 0.0216 0.4433 1.6287 0.0179 0.4979 29
1.8477 0.0220 0.4274 1.6129 0.0180 0.4896 30
1.7778 0.0224 0.4123 1.5705 0.0182 0.4769 31
1.6924 0.0228 0.3980 1.5096 0.0185 0.4666 32
1.6389 0.0231 0.3847 1.4837 0.0186 0.4558 33
1.5687 0.0235 0.3710 1.4419 0.0188 0.4475 34
1.4742 0.0242 0.3566 1.4365 0.0188 0.4385 35
1.4321 0.0244 0.3452 1.4011 0.0190 0.4300 36
1.3712 0.0248 0.3328 1.4145 0.0189 0.4245 37
1.3249 0.0251 0.3231 1.3604 0.0192 0.4188 38
1.2787 0.0253 0.3113 1.3424 0.0193 0.4133 39
1.1978 0.0259 0.2997 1.3275 0.0194 0.4068 40
1.1643 0.0261 0.2893 1.3122 0.0195 0.4019 41
1.1043 0.0266 0.2785 1.3011 0.0195 0.3964 42
1.0828 0.0267 0.2712 1.3235 0.0195 0.3932 43
1.0231 0.0272 0.2601 1.2947 0.0196 0.3873 44

Framework versions