generated_from_keras_callback

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whisper_syl_cv12_pad_lob100__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
5.0233 0.0115 1.6383 3.8616 0.0117 0.9516 0
4.4412 0.0127 0.8560 3.5410 0.0125 0.8971 1
4.0719 0.0138 0.8366 3.2944 0.0132 0.8706 2
3.8091 0.0146 0.8133 3.1691 0.0134 0.8487 3
3.6239 0.0152 0.7866 3.0647 0.0136 0.8282 4
3.4749 0.0156 0.7589 2.9835 0.0139 0.8049 5
3.3444 0.0161 0.7359 2.9351 0.0140 0.7979 6
3.2215 0.0165 0.7138 2.8468 0.0145 0.7589 7
3.0754 0.0172 0.6873 2.7530 0.0148 0.7413 8
2.8713 0.0181 0.6484 2.5226 0.0157 0.7017 9
2.5469 0.0197 0.5934 2.1931 0.0168 0.6285 10
2.0233 0.0225 0.4997 1.6411 0.0189 0.5215 11
1.3808 0.0264 0.3852 1.2401 0.0205 0.4238 12
0.9722 0.0290 0.3123 1.0195 0.0215 0.3682 13
0.7388 0.0305 0.2828 0.8773 0.0221 0.3322 14
0.5787 0.0317 0.2751 0.7970 0.0225 0.3083 15
0.4642 0.0325 0.2878 0.7315 0.0227 0.2964 16
0.3752 0.0332 0.4217 0.6897 0.0229 0.3297 17
0.3042 0.0338 0.7294 0.6572 0.0231 0.4453 18
0.2444 0.0343 1.1298 0.6369 0.0232 0.6637 19
0.1949 0.0348 1.6370 0.6180 0.0233 1.6119 20
0.1544 0.0352 1.6151 0.6149 0.0233 1.6843 21
0.1212 0.0355 1.3832 0.6066 0.0233 0.8721 22
0.0931 0.0357 1.2799 0.6034 0.0234 0.5109 23
0.0725 0.0359 1.0940 0.6102 0.0234 1.0111 24
0.0551 0.0361 1.2865 0.6000 0.0234 1.1393 25
0.0411 0.0361 1.8511 0.6037 0.0235 2.0574 26
0.0311 0.0362 1.7179 0.6018 0.0235 1.4847 27
0.0253 0.0362 0.9801 0.6010 0.0235 0.4457 28
0.0231 0.0362 0.9376 0.6046 0.0235 0.9247 29
0.0196 0.0362 0.6466 0.6078 0.0235 0.5271 30
0.0177 0.0362 0.4041 0.6155 0.0235 0.4352 31
0.0139 0.0362 0.4202 0.6037 0.0236 0.5585 32
0.0137 0.0362 0.8151 0.6015 0.0236 1.8476 33
0.0122 0.0362 3.4515 0.6043 0.0236 3.8210 34
0.0098 0.0362 1.1787 0.5985 0.0236 0.8094 35
0.0071 0.0362 0.9920 0.5992 0.0236 0.8755 36
0.0055 0.0362 2.4665 0.6047 0.0236 2.0127 37
0.0124 0.0362 4.2468 0.6089 0.0236 2.8886 38
0.0109 0.0362 2.0177 0.6097 0.0236 0.3417 39
0.0073 0.0362 0.9927 0.6057 0.0237 2.5519 40
0.0080 0.0362 1.7341 0.6099 0.0236 1.3119 41
0.0063 0.0362 2.4288 0.6058 0.0237 1.3465 42
0.0038 0.0362 1.4535 0.6022 0.0237 1.6804 43
0.0028 0.0362 2.2629 0.6001 0.0238 3.4388 44
0.0021 0.0362 3.5877 0.6018 0.0238 2.6165 45
0.0017 0.0362 3.0080 0.6043 0.0238 2.6827 46
0.0061 0.0362 2.5182 0.6545 0.0235 0.2316 47
0.0126 0.0362 0.2097 0.6206 0.0236 0.6194 48
0.0071 0.0362 0.3045 0.6047 0.0237 0.7476 49

Framework versions