Pretrained Chromoformer weights

Pretrained weights for Chromoformer models. Models were individually trained for 11 cell types from Roadmap Epigenomics Project. For each cell type, 18955 protein coding genes were divided into four non-overlapping cross-validation (CV) sets, and trained weights for each cross-validation fold is provided in this dataset.<br>The directory is organized firstly by Roadmap Epigenomics cell type (using corresponding EID), and four pytorch checkpoint files (a .pt file for each CV-fold) are placed in each directory.<br>'*.pt' files are basically dictionaries containing pretrained weights as well as some training details associated with the following keys:<br>- 'net' : Pretrained weights- 'optimizer': Status of pytorch optimizer at the time of model snapshot.- 'epoch': Epoch at the time of model snapshot.- 'last_val_loss': Validation loss at the time of model snapshot.- 'last_val_auc': Validation AUC at the time of model snapshot.- 'val_score': Output probabilities for genes in validation set.- 'val_label': True labels for genes in validation set.