Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_randomf4_20261105-041806

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
train0.33290.95490.94390.91122750.00000.1224559.00000.80000.24220.51660.00000.00000.70080.74000.20590.86010.04000.00000.75270.74000.18770.87440.09000.00000.78340.76730.16510.87440.13060.00000.8254
validation0.41770.94350.93200.8892851.00000.079035.00000.80000.21610.73310.10000.00000.79400.62000.12620.86980.14000.00000.81080.63000.08620.86980.13000.00000.82730.67070.10800.86980.12200.00000.8266
test0.41840.94280.93130.8879915.0000-0.0003570.00000.60000.00930.64430.00000.00000.67640.72000.11110.70360.06000.00000.78060.64000.06370.70400.09000.00000.79840.64630.08280.70400.08540.00000.7955

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_randomf4
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: random
  split_fold: 4
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