README.md

metadata

license: mit

ESM-2 Full Finetune for Binding Sites

This model is a full finetune of ESM-2, to illustrate how full finetuning overfits and generalizes quite poorly compared to LoRA and QLoRA finetuning. This model was finetuned on the 600K dataset. We also note that on the 24GB A10 GPU, the batch size has to be significantly smaller. To finetune a similar model, use this script.

Train metrics:

{'eval_loss': 0.13651661574840546,
'eval_accuracy': 0.9656322509450104,
'eval_precision': 0.38616650354104665,
'eval_recall': 0.9618091516702236,
'eval_f1': 0.55107594226701,
'eval_auc': 0.9637635647574605,
'eval_mcc': 0.5977943918337999}

Test metrics:

{'eval_loss': 0.2910114824771881,
'eval_accuracy': 0.923270649115702,
'eval_precision': 0.14887069127765168,
'eval_recall': 0.533511928419524,
'eval_f1': 0.23278520670392827,
'eval_auc': 0.7327381144575454,
'eval_mcc': 0.25329082069818704}