Protein Engineering

gb1 · Fully connected

reference_gb1_fc_plm_contiguousf2_20261104-184444

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
train0.23770.96680.97760.927640274.00000.7655709.00001.00001.26461.43460.00000.00000.85871.00001.21401.45260.12000.00000.90681.00001.17261.46360.26000.00000.92500.99790.85791.87050.56990.00000.9523
validation7.72440.34940.3383-0.40842473.00000.04286954.00000.7000-0.61891.02550.00000.00000.56110.5200-0.98801.40540.00000.00000.49570.5100-1.03791.40540.01000.00000.49220.4950-1.10671.40540.01000.00000.4876
test8.44370.30680.2665-0.56532092.0000-0.01328048.00000.7000-0.44631.37580.00000.00000.58320.4800-1.00171.45750.00000.00000.49660.4800-1.09241.63660.01000.00000.48900.4179-1.33461.63660.06470.00000.4537

Loss per epoch

training validation

Config

name: reference_gb1_fc_plm_contiguousf2
task: dms
data:
  dataset: gb1
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
model:
  name: fcn
  hidden:
  - 1000
  dropout: 0.2
train:
  epochs: 300
  batch_size: 64
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7