base_model: westlake-repl/SaProt_35M_AF2
library_name: peft
Model Card for Model ID
This model is used to predict mutation fitness score of protein PTEN_HUMAN (Phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-specificity protein phosphatase). Dual-specificity protein phosphatase, dephosphorylating tyrosine-, serine- and threonine-phosphorylated proteins. Also functions as a lipid phosphatase, removing the phosphate in the D3 position of the inositol ring of PtdIns(3,4,5)P3/phosphatidylinositol 3,4,5-trisphosphate, PtdIns(3,4)P2/phosphatidylinositol 3,4-diphosphate and PtdIns3P/phosphatidylinositol 3-phosphate with a preference for PtdIns(3,4,5)P3. Furthermore, this enzyme can also act as a cytosolic inositol 3-phosphatase acting on Ins(1,3,4,5,6)P5/inositol 1,3,4,5,6 pentakisphosphate and possibly Ins(1,3,4,5)P4/1D-myo-inositol 1,3,4,5-tetrakisphosphate.
Task type
protein level regression
Dataset description
The dataset is from Deep generative models of genetic variation capture the effects of mutations.
Model input type
Amino acid sequence
Performance
0.62 Spearman's ρ
LoRA config
lora_dropout: 0.0
lora_alpha: 16
target_modules: ["query", "key", "value", "intermediate.dense", "output.dense"]
modules_to_save: ["classifier"]
Training config
class: AdamW
betas: (0.9, 0.98)
weight_decay: 0.01
learning rate: 1e-4
epoch: 50
batch size: 64
precision: 16-mixed