SaProtHub/Model-Signal-Peptides-Prediction-650M

Base model: westlake-repl/SaProt_650M_AF2

Model Card for Model ID

This model is used to predict signal peptides on each site of amino acid sequences.

Task type

Residue level clssification

Dataset description

The dataset is from SignalP 6.0 predicts all five types of signal peptides using protein language models. This dataset contains 7 classes:

S (0): Sec/SPI signal peptide | T (1): Tat/SPI or Tat/SPII signal peptide | L (2): Sec/SPII signal peptide | P (3): Sec/SPIII signal peptide | I (4): cytoplasm | M (5): transmembrane | O (6): extracellular

Model input type

Amino acid sequence

Performance

test_acc: 0.96

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: 10

batch size: 100

precision: 16-mixed