Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_plm_contiguousf0_20261104-175425

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
train1.84550.28390.20960.07206904.0000-0.068311557.00000.60000.41612.14660.00000.00000.20870.54000.25642.14660.00000.00000.17750.54000.15862.20540.00000.00000.15330.53220.07172.50020.02340.00000.1286
validation1.49810.31010.29180.09561203.00000.00421862.00000.50000.46092.01740.00000.00000.28410.48000.18592.31360.04000.00000.20130.39000.05172.31360.03000.00000.15890.47060.20862.31360.02940.00000.2039
test1.92810.32050.30460.03791218.0000-0.0446776.00000.50000.32072.20540.00000.00000.28470.4000-0.02312.20540.04000.00000.21990.4000-0.00052.65740.06000.00000.24510.4186-0.07742.20540.02330.00000.1986

Loss per epoch

training validation

Config

name: reference_bgl3_fc_plm_contiguousf0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 0
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