Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_contiguousf1_20261104-154008

Metrics

Setmsepearsonrspearmanrr2above_wt_nabove_wt_spearmanrbudget_to_maxhit_rate_at_10mean_at_10max_at_10precision_at_10captured_at_10hit_rate_at_50mean_at_50max_at_50precision_at_50captured_at_50hit_rate_at_100mean_at_100max_at_100precision_at_100captured_at_100hit_rate_at_1pctmean_at_1pctmax_at_1pctprecision_at_1pctcaptured_at_1pct
train1.89290.51440.49420.03245657.00000.10748087.00001.00001.41893.11600.10000.50800.80000.69793.11600.02000.34120.79000.67463.11600.01000.35530.72670.59433.11600.03330.3400
validation2.1365-0.0841-0.0819-0.00071465.0000-0.0581429.00000.2000-1.57971.21500.00000.0000-0.33450.2000-1.52041.59450.00000.0000-0.35830.2600-1.24292.20540.01000.0000-0.27980.2326-1.42711.59450.00000.0000-0.3211
test1.6792-0.0346-0.0521-0.01371203.0000-0.01313014.00000.40000.03071.69460.00000.00000.12780.4400-0.04102.14660.02000.00000.11120.3800-0.26912.14660.01000.00000.02220.4412-0.10122.14660.02940.00000.0847

Loss per epoch

training validation

Config

name: reference_bgl3_fc_contiguousf1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: contiguous
  split_fold: 1
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