Protein Engineering

bgl3 · Linear

reference_bgl3_lr_plm_contiguousf3_20261105-040539

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
train1.37720.57370.54720.30164815.00000.14534112.00000.80001.00371.69460.00000.00000.41900.82001.03462.36370.02000.00000.48600.81000.88572.36370.03000.00000.46250.79710.87382.36370.02900.00000.4716
validation1.69310.22170.17840.04661997.0000-0.1214605.00000.7000-0.09111.35810.00000.00000.03300.5000-0.01382.36370.04000.00000.06790.55000.02972.36370.02000.00000.09060.4681-0.04252.36370.04260.00000.0565
test1.84630.23730.18440.04671899.0000-0.06924204.00000.50000.27281.78560.00000.00000.17490.50000.14622.20540.00000.00000.15540.53000.14592.20540.01000.00000.16590.51020.16992.20540.00000.00000.1637

Loss per epoch

training validation

Config

name: reference_bgl3_lr_plm_contiguousf3
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 3
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.0001
  patience: 15
  min_delta: 1.0e-05
  seed: 7