Protein Engineering

bgl3 · Linear

reference_bgl3_lr_modulof1_20261104-153413

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
train1.52770.47740.45090.14433546.00000.12763913.00000.70000.55121.48330.00000.26890.74000.63182.36370.02000.33630.71000.59712.45670.04000.34660.71720.61342.45670.04040.3521
validation1.5744-0.0295-0.0179-0.0214432.0000-0.0519180.00000.2000-1.43781.04800.00000.0000-0.31720.2800-0.85142.14660.04000.0000-0.12940.3300-0.55512.14660.08000.0000-0.00960.2941-1.11072.14660.05880.0000-0.2098
test1.57220.07410.0771-0.0043424.0000-0.0185432.00000.40000.19411.86900.00000.00000.21790.3400-0.17321.94590.04000.00000.10700.3800-0.10812.08410.14000.00000.15000.40000.09081.86900.00000.00000.1880

Loss per epoch

training validation

Config

name: reference_bgl3_lr_modulof1
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index
  split_dir: null
  split_scheme: modulo
  split_fold: 1
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7