Protein Engineering

bgl3 · Sequence CNN

reference_bgl3_cnn_plm_modulof0_20261104-175018

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10tie_share_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50tie_share_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100tie_share_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pcttie_share_at_1pctcaptured_at_1pct
train1.30580.53360.48990.27373841.00000.09153026.00001.00001.54182.54190.00000.00000.57780.84001.01602.54190.04000.00000.47060.76000.83012.54190.05000.00000.43040.76360.83292.54190.05450.00000.4351
validation1.31470.41190.36420.1602424.0000-0.0694258.00000.40000.09031.21500.00000.00000.18210.40000.10652.41130.06000.00000.22020.49000.24572.41130.16000.00000.31120.3333-0.03851.21500.00000.00000.1420
test1.38040.30910.31570.0836338.0000-0.14591057.00000.2000-1.16921.35810.00000.0000-0.22030.2200-0.94422.01740.04000.0000-0.16090.3100-0.56212.36370.10000.00000.00170.2308-0.98672.01740.07690.0000-0.1566

Loss per epoch

training validation

Config

name: reference_bgl3_cnn_plm_modulof0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 0
model:
  name: cnn
  conv:
  - - 32
    - 17
  hidden:
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7