Protein Engineering

pab1 · Fully connected

reference_pab1_fc_plm_contiguousf0_20261104-175737

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
train0.38380.94310.90470.88193428.00000.06161476.00000.90000.21530.51660.00000.00000.63700.82000.19530.86010.02000.00000.69610.78000.17080.86980.05000.00000.71910.71430.14031.08960.07790.00000.7541
validation1.79660.71470.68940.4995196.00000.04101571.00000.1000-0.30950.09160.00000.00000.68150.1400-0.42310.22320.02000.00000.68790.2200-0.44050.32240.09000.00000.70470.1250-0.38110.22320.00000.00000.6803
test1.98330.72580.72870.4649222.0000-0.02662038.00000.2000-0.25350.06340.00000.00000.76200.2000-0.28620.23730.02000.00000.78810.1800-0.36990.37230.06000.00000.78420.2041-0.28560.23730.02040.00000.7876

Loss per epoch

training validation

Config

name: reference_pab1_fc_plm_contiguousf0
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  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