Protein Engineering

pab1 · Fully connected

reference_pab1_fc_s4_20261104-135427

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
test0.50500.93230.91560.8672477.00000.1262601.00000.6000-0.16580.56280.00000.00000.62900.64000.06520.84200.16000.00000.79800.65000.06280.85050.23000.00000.83650.60980.01950.84200.14630.00000.7681
train0.41120.94530.93020.89063650.00000.183411907.00000.60000.13250.97410.00000.66670.72000.18250.98160.10000.74460.64000.13190.98160.06000.75880.68880.12231.07020.13600.8151
validation0.46780.93380.91680.8709389.00000.0823754.00000.4000-0.29390.39450.00000.00000.58430.4000-0.08430.86620.14000.00000.73790.4500-0.07580.86620.15000.00000.77920.4865-0.06800.86620.08110.00000.7274

Loss per epoch

training validation

Config

name: reference_pab1_fc_s4
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: pab1/splits/main
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: 4