devlog#4, also again long time no see, been really busy with bunch of school works, but still also a bit of development almost everyday so here i modify the refseqs requests only 25 organisms and 6 genomes for each organism, also modified bunch of files to support the new refseqs.json style, and also trained the classifier model many mistakes and 100minutes * 10 epoch = 1000 minutes totaling, take so long to finish (around 16.67 hours *no more 67 atp) the model itself has 4 conv1d blocks and 2 layers of transformer, and the dataset itself has ~523M tokens (as of i remember) and the output is astonishing, as you can see in the image below, 0.062 loss, 98.11% accuracy, and validation loss of 0.7708, and validation accuracy of 88.84% (although it has 9% gap between acc and vacc but still nevermind this aint production grade and should not be use in production or other associated) also i test it with test data (from the dataloader split) and other dataset with the same organism but different genomes, i got avg loss at ~1.25 and avg test accuracy at ~82% pretty gooddd, that’s all for now, next is like genomic analysis, like promoter region prediction and open reading frame prediction (ORF) (for finding a sequence that potentially encodes a protein) and done genomes-level prediction and out off 306 genomes, got 292 correct which is 95.42% holy really welllllllllll!!!
