generated_from_keras_callback

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whisper_input_decoder_no_lob_with_force__0025

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

Framework versions