Protein Engineering

bgl3 · Fully connected

reference_bgl3_fc_mr5plm_contiguousf0_20261104-222338

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
train1.86540.47220.49310.0521156.0000-0.0532539.00000.2000-0.66830.21730.00000.00000.42080.1000-1.00520.39610.04000.00000.32920.0900-0.93950.76300.06000.00000.38560.1143-0.98050.21730.00000.00000.3296
validation0.88860.64230.66990.380740.00000.0798248.00000.0000-1.1060-0.01360.00000.00000.08300.0800-0.60040.19870.12000.00000.46940.1000-0.48730.40080.26000.00000.60100.0000-1.2015-0.01360.00000.00000.0266
test1.47930.53900.57640.128821.0000-0.1916177.00000.0000-0.6726-0.11540.00000.00000.53590.0800-0.76100.20190.10000.00000.56830.0500-0.90070.20190.26000.00000.52760.0000-0.8478-0.11540.00000.00000.4614

Loss per epoch

training validation

Config

name: reference_bgl3_fc_mr5plm_contiguousf0
task: dms
data:
  dataset: bgl3
  encoding: one_hot,aa_index,plm,plm_sum
  split_dir: null
  split_scheme: contiguous
  split_fold: 0
  min_reads: 5
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