Protein Engineering

pab1 · Linear

reference_pab1_lr_s3_20261104-022652

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
test0.73690.89790.90140.8062477.00000.1372549.00000.4000-0.21120.51660.00000.00000.61270.62000.04211.16150.14000.00000.78870.63000.01091.16150.29000.00000.81460.65850.06711.16150.17070.00000.7869
train0.66250.90760.91580.82373650.00000.21020.10000.71330.16000.77610.11000.77490.16010.8103
validation0.69220.89940.90340.8090389.00000.1136490.00000.4000-0.28270.35770.00000.00000.58840.4800-0.18100.59820.08000.00000.69820.4800-0.14570.86620.18000.00000.74910.4595-0.15430.59820.05410.00000.6927

Loss per epoch

training validation

Config

name: reference_pab1_lr_s3
task: dms
data:
  dataset: pab1
  encoding: one_hot,aa_index
  split_dir: pab1/splits/main
model:
  name: lr
train:
  epochs: 300
  batch_size: 128
  learning_rate: 0.001
  patience: 15
  min_delta: 1.0e-05
  seed: 3