Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_mr5plm_modulof1_20261104-222455

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
train1.21240.50890.51890.2372136.00000.0975785.00000.2000-1.03820.21730.00000.00000.16160.0800-0.96730.39610.04000.00000.22830.0700-1.03990.76300.06000.00000.19960.1481-0.97780.39610.03700.00000.2086
validation0.93660.45040.51680.202823.0000-0.2476155.00000.0000-1.5192-0.04550.00000.0000-0.30200.0600-0.94590.14210.12000.00000.13750.0700-0.69280.14480.30000.00000.38400.0000-1.5283-0.04550.00000.0000-0.3021
test0.75220.59720.61260.333547.0000-0.1836120.00000.0000-0.1860-0.01360.00000.00000.52310.1400-0.31580.20190.18000.00000.58040.1400-0.32470.22160.29000.00000.63520.0000-0.1720-0.01360.00000.00000.4948

Loss per epoch

training validation

Config

name: reference_bgl3_fc_mr5plm_modulof1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 1
  min_reads: 5
model:
  name: fcn
  hidden:
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 32
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7