Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_randomf0_20261104-174731

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
train0.33830.95390.94290.90972767.00000.07552196.00000.90000.24810.51660.00000.00000.71080.80000.17650.83230.02000.00000.74760.80000.20551.16150.07000.00000.79320.74290.14321.16150.13470.00000.8184
validation0.39420.94620.93320.8946898.00000.08902040.00000.70000.07960.48350.00000.00000.68420.76000.15100.86010.08000.00000.79060.75000.12120.86010.09000.00000.81760.73170.11940.86010.07320.00000.8052
test0.41710.94330.93140.8894851.00000.036228.00000.70000.23700.73310.10000.00000.80170.76000.16480.86980.08000.00000.82600.72000.11970.86980.11000.00000.84110.70730.11420.86980.07320.00000.8291

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_randomf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 0
model:
  name: fcn
  hidden:
  - 100
  - 100
  - 100
  dropout: 0.2
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 7