Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_contiguousf2_20261104-184725

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
train0.59210.93120.92700.83801747.00000.0980993.00001.00000.22530.51660.00000.00000.73830.66000.08530.87440.02000.00000.75600.63000.07540.87440.08000.00000.78500.58890.03340.87440.06670.00000.7986
validation0.79600.82920.69960.6863383.0000-0.04151996.00000.1000-0.29070.01380.00000.00000.45140.2000-0.21510.46370.04000.00000.56220.2100-0.18960.49740.08000.00000.62470.1562-0.22790.43330.00000.00000.5319
test1.79800.76400.78010.5767475.0000-0.06651400.00000.2000-0.16350.07380.00000.00000.71750.2400-0.10620.52260.06000.00000.79220.2500-0.13020.52260.04000.00000.81130.2500-0.10590.52260.06250.00000.7908

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_contiguousf2
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
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