generated_from_keras_callback

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whisper_charsplit_new_round4__0035

This model is a fine-tuned version of bigmorning/whisper_charsplit_new_round2__0061 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
0.0009 0.0795 7.9702 0.5713 0.0770 6.9300 0
0.0011 0.0795 7.7485 0.5743 0.0771 6.6465 1
0.0011 0.0795 8.1600 0.5748 0.0771 7.1363 2
0.0008 0.0795 8.1954 0.5845 0.0770 7.1869 3
0.0009 0.0795 8.4533 0.5771 0.0771 7.4112 4
0.0009 0.0795 8.3048 0.5912 0.0770 6.5276 5
0.0008 0.0795 8.2183 0.5810 0.0771 7.1210 6
0.0011 0.0795 8.3785 0.5861 0.0770 7.6613 7
0.0010 0.0795 8.0860 0.5811 0.0771 7.0809 8
0.0009 0.0795 8.2523 0.5894 0.0770 7.1269 9
0.0006 0.0795 8.7530 0.5819 0.0771 7.3657 10
0.0007 0.0795 8.5391 0.5773 0.0771 7.7370 11
0.0010 0.0795 8.8222 0.5894 0.0770 7.9252 12
0.0014 0.0795 8.9039 0.5880 0.0771 7.6404 13
0.0009 0.0795 8.6866 0.5777 0.0771 7.5804 14
0.0006 0.0795 9.0833 0.5736 0.0772 8.3242 15
0.0003 0.0795 9.3697 0.5732 0.0772 8.4795 16
0.0006 0.0795 9.4161 0.5838 0.0771 8.5173 17
0.0011 0.0795 9.7801 0.5967 0.0769 8.5462 18
0.0016 0.0795 9.9252 0.5824 0.0771 8.8226 19
0.0009 0.0795 10.1258 0.5813 0.0771 8.6993 20
0.0006 0.0795 9.8897 0.5784 0.0772 8.1699 21
0.0009 0.0795 9.3199 0.5971 0.0771 7.6986 22
0.0018 0.0795 10.2724 0.5924 0.0769 8.9443 23
0.0012 0.0795 9.5275 0.5783 0.0771 7.7057 24
0.0010 0.0795 8.6555 0.5738 0.0772 7.1508 25
0.0005 0.0795 8.8172 0.5775 0.0772 6.9496 26
0.0005 0.0795 8.4569 0.5860 0.0771 7.5262 27
0.0012 0.0795 9.6634 0.5917 0.0770 8.3290 28
0.0011 0.0795 8.9484 0.5855 0.0771 7.6950 29
0.0007 0.0795 8.7377 0.5882 0.0771 7.4076 30
0.0005 0.0795 8.5209 0.5855 0.0772 6.7134 31
0.0009 0.0795 8.5136 0.5862 0.0771 8.0204 32
0.0011 0.0795 7.8920 0.5788 0.0772 7.3091 33
0.0008 0.0795 8.8453 0.5776 0.0772 7.0827 34

Framework versions