Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_plm_contiguousf2_20261104-184410

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
train1.43460.51450.45940.23154995.00000.02124005.00000.80001.13033.11600.10000.00000.43720.76000.89913.11600.02000.00000.42530.69000.59953.11600.04000.00000.34430.63970.50303.11600.03680.00000.3177
validation1.78100.29020.18790.08051899.0000-0.08193031.00000.5000-0.50831.59450.00000.0000-0.07100.5600-0.13102.08410.00000.00000.05500.4800-0.29972.50020.03000.0000-0.00660.5714-0.12852.08410.00000.00000.0558
test2.08000.18970.11260.02581465.0000-0.03931534.00000.1000-0.45090.38470.00000.00000.01340.4200-0.37632.14660.02000.00000.04130.3700-0.47172.31360.03000.00000.00850.4651-0.15952.14660.00000.00000.1153

Loss per epoch

training validation

Config

name: reference_bgl3_fc_plm_contiguousf2
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 2
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