Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_plm_modulof3_20261105-035856

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
train1.55830.48090.46210.20343467.00000.03042545.00000.40000.11831.94590.00000.00000.15990.62000.51842.26100.00000.00000.32020.70000.54462.36370.03000.00000.34700.69700.54152.36370.03030.00000.3455
validation1.23420.29830.27570.0883437.0000-0.11761199.00000.30000.08181.69460.00000.00000.16690.3200-0.06492.20540.06000.00000.13880.3100-0.08412.20540.09000.00000.14470.25000.02111.69460.00000.00000.1533
test1.28130.27340.22860.0707437.0000-0.1308456.00000.4000-0.41142.23910.00000.00000.00050.3600-0.22322.23910.06000.00000.07740.3300-0.16162.23910.04000.00000.11620.4375-0.34572.23910.06250.00000.0229

Loss per epoch

training validation

Config

name: reference_bgl3_fc_plm_modulof3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: modulo
  split_fold: 3
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