M2 - small CNN trained on embeddings

The model is trained on ProtBert-BFD embeddings of knots_AF dataset to recognize between knotted and unknotted proteins based on their amino acid sequence.

Accuracy on the test set:

	Dataset size	Unknotted set size	Accuracy	TPR	TNR
All	39412	19718	0.9690	0.9569	0.9811
SPOUT	7371	550	0.9712	0.9815	0.8436
TDD	612	24	0.9673	0.9796	0.6667
DUF	716	429	0.9413	0.8955	0.9720
AdoMet synthase	1794	240	0.9727	0.9755	0.9542
Carbonic anhydrase	1531	539	0.8870	0.8619	0.9332
UCH	477	125	0.8700	0.8892	0.816
ATCase/OTCase	3799	3352	0.9932	0.9418	1.0
ribosomal-mitochondrial	147	41	0.8163	0.8319	0.7805
membrane	8309	1577	0.9740	0.9857	0.9239
VIT	14347	12639	0.9742	0.8214	0.9948
biosynthesis of lantibiotics	392	286	0.9388	0.8019	0.9895