trial_id stringlengths 104 182 | experiment_name stringclasses 1
value | sweep_name stringclasses 3
values | combo_name stringlengths 72 151 | grid_overrides stringlengths 60 187 | job_id stringclasses 3
values | cluster stringclasses 1
value | timestamp stringlengths 32 32 | config_yaml stringlengths 4.29k 4.54k | best_val_loss float64 0.11 0.42 | best_val_pearson_r float64 0.76 0.95 | best_epoch int64 13 149 | sim_r2 float64 0.58 0.89 | sim_pearson_r float64 0.76 0.95 | sim_mean_gt_z_abs_ratio float64 0 0.17 | sim_mean_model_z_abs_ratio float64 0 0.32 | sim_z_abs_1_corr float64 0.21 0.99 | sim_z_abs_2_corr float64 0.07 0.36 ⌀ | sim_z_abs_ratio_corr float64 0.06 0.56 ⌀ | sim_z_abs_ratio_mse float64 0 0.13 | absorption_gap float64 -0.16 0.32 | promiscuity_mean_entropy float64 0.11 0.49 ⌀ | promiscuity_max_entropy float64 0.6 0.99 ⌀ | n_true_interaction_pairs float64 0 3 | interaction_effective_num_pairs float64 1 37.9 | interaction_concentration_gap float64 -1.01 37.9 | epoch_history stringlengths 32.1k 329k | wandb_run_url stringlengths 52 52 | report_pdf_path stringlengths 218 297 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
20260710_firstorder_synccanary__20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0 | fnbm-current | 20260710_firstorder_synccanary | 20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0 | {"model.kwargs.interaction_coefficient_group_l1_penalty": 0} | 13268200 | torch | 2026-07-10T15:43:20.942004+00:00 | data:
batch_size: 128
downstream_sequence: ''
num_workers: 2
pin_memory: true
sequence_column: sequence
target_column: label
test_csv: /scratch/abr10036/projects/2025-interactions/datasets/202607_simulations/20260707_first_order/test.csv
train_csv: /scratch/abr10036/projects/2025-interactions/datasets/2... | 0.416264 | 0.764633 | 14 | 0.582292 | 0.764633 | 0 | 0.322472 | 0.214659 | null | null | 0.133637 | 0.322472 | 0.493423 | 0.950296 | 0 | 37.865402 | 37.865402 | [{"epoch": 0, "train_loss": 0.9912525415420532, "val_loss": 0.9611283802682427, "val_pearson_r": 0.20023013651371002, "lr": 0.0005, "epoch_time_s": 35.89, "grad_norm_mean": 0.7054833173751831, "grad_norm_max": 3.9280409812927246, "reg_conv_kernel_l1_raw": 44.472137451171875, "reg_conv_kernel_l1_scaled": 0.0, "reg_conv_... | https://wandb.ai/arushml/FactorizedNBM/runs/ao9u2t1t | /scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_synccanary/20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0/interpretation/epoch_14/simulation_identifiability/report.pdf |
20260710_firstorder_synccanary__20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0.0001 | fnbm-current | 20260710_firstorder_synccanary | 20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0.0001 | {"model.kwargs.interaction_coefficient_group_l1_penalty": 0.0001} | 13268200 | torch | 2026-07-10T15:52:55.077214+00:00 | data:
batch_size: 128
downstream_sequence: ''
num_workers: 2
pin_memory: true
sequence_column: sequence
target_column: label
test_csv: /scratch/abr10036/projects/2025-interactions/datasets/202607_simulations/20260707_first_order/test.csv
train_csv: /scratch/abr10036/projects/2025-interactions/datasets/2... | 0.410285 | 0.767837 | 13 | 0.586704 | 0.779163 | 0 | 0.272775 | 0.235365 | null | null | 0.098228 | 0.272775 | 0.466379 | 0.943202 | 0 | 35.02229 | 35.02229 | [{"epoch": 0, "train_loss": 0.9912760257720947, "val_loss": 0.9611749516171255, "val_pearson_r": 0.20003849267959595, "lr": 0.0005, "epoch_time_s": 50.66, "grad_norm_mean": 0.7055649161338806, "grad_norm_max": 3.9280409812927246, "reg_conv_kernel_l1_raw": 44.45408630371094, "reg_conv_kernel_l1_scaled": 0.0, "reg_conv_k... | https://wandb.ai/arushml/FactorizedNBM/runs/71uoykh0 | /scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_synccanary/20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty0.0001/interpretation/epoch_14/simulation_identifiability/report.pdf |
20260710_firstorder_synccanary__20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty1e-5 | fnbm-current | 20260710_firstorder_synccanary | 20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty1e-5 | {"model.kwargs.interaction_coefficient_group_l1_penalty": 1e-05} | 13268200 | torch | 2026-07-10T15:48:06.033082+00:00 | data:
batch_size: 128
downstream_sequence: ''
num_workers: 2
pin_memory: true
sequence_column: sequence
target_column: label
test_csv: /scratch/abr10036/projects/2025-interactions/datasets/202607_simulations/20260707_first_order/test.csv
train_csv: /scratch/abr10036/projects/2025-interactions/datasets/2... | 0.411412 | 0.76772 | 14 | 0.587277 | 0.76772 | 0 | 0.321474 | 0.222098 | null | null | 0.132865 | 0.321474 | 0.490315 | 0.947438 | 0 | 37.229824 | 37.229824 | [{"epoch": 0, "train_loss": 0.9912598133087158, "val_loss": 0.9611444594753775, "val_pearson_r": 0.2001277655363083, "lr": 0.0005, "epoch_time_s": 50.32, "grad_norm_mean": 0.7055728435516357, "grad_norm_max": 3.9280409812927246, "reg_conv_kernel_l1_raw": 44.453514099121094, "reg_conv_kernel_l1_scaled": 0.0, "reg_conv_k... | https://wandb.ai/arushml/FactorizedNBM/runs/018k7qw6 | /scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_synccanary/20260710_firstorder_synccanary-interaction_coefficient_group_l1_penalty1e-5/interpretation/epoch_14/simulation_identifiability/report.pdf |
"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.001-order2_contributio(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.001, \"model.kwargs.(...TRUNCATED) | 13305710 | torch | 2026-07-11T03:17:25.296663+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.168944 | 0.911326 | 109 | 0.830466 | 0.911322 | 0 | 0 | 0.726262 | null | null | 0 | 0 | null | null | 0 | 1 | 1 | "[{\"epoch\": 0, \"train_loss\": 0.9663487076759338, \"val_loss\": 0.8846952501375964, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/t5yqygrs | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.001-order2_contributio(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.001, \"model.kwargs.(...TRUNCATED) | 13305710 | torch | 2026-07-11T03:19:11.571067+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.118705 | 0.938552 | 134 | 0.88082 | 0.938547 | 0 | 0 | 0.661489 | null | null | 0 | 0 | null | null | 0 | 1 | 1 | "[{\"epoch\": 0, \"train_loss\": 0.9787513613700867, \"val_loss\": 0.8996884800066614, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/qpy5m6b3 | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.001-order2_contributio(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.001, \"model.kwargs.(...TRUNCATED) | 13305710 | torch | 2026-07-11T03:22:04.805002+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.10814 | 0.944188 | 117 | 0.891314 | 0.944116 | 0 | 0.061593 | 0.883633 | null | null | 0.020887 | 0.061593 | 0.259459 | 0.968246 | 0 | 1.899492 | 1.899492 | "[{\"epoch\": 0, \"train_loss\": 0.9665890336036682, \"val_loss\": 0.8780847317094256, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/tv3bjzel | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.001-order2_contributio(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.001, \"model.kwargs.(...TRUNCATED) | 13305710 | torch | 2026-07-11T03:22:13.883213+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.115199 | 0.940391 | 148 | 0.884309 | 0.940384 | 0 | 0 | 0.707982 | null | null | 0 | 0 | 0.213673 | 0.97762 | 0 | 3.484336 | 3.484336 | "[{\"epoch\": 0, \"train_loss\": 0.9788815379142761, \"val_loss\": 0.9016267471252732, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/yq0c987j | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
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"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.0005-order2_contributi(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.0005, \"model.kwargs(...TRUNCATED) | 13305710 | torch | 2026-07-11T04:05:11.674544+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.171784 | 0.909696 | 145 | 0.827446 | 0.909665 | 0 | 0 | 0.66939 | null | null | 0 | 0 | 0.275568 | 0.923348 | 0 | 5.15468 | 5.15468 | "[{\"epoch\": 0, \"train_loss\": 0.9787137508392334, \"val_loss\": 0.9021147147865053, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/2u28udok | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
"20260710_firstorder_finegrid__20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_p(...TRUNCATED) | fnbm-current | 20260710_firstorder_finegrid | "20260710_firstorder_finegrid-seed0-interaction_coefficient_group_l1_penalty0.0005-order2_contributi(...TRUNCATED) | "{\"run.seed\": 0, \"model.kwargs.interaction_coefficient_group_l1_penalty\": 0.0005, \"model.kwargs(...TRUNCATED) | 13305710 | torch | 2026-07-11T04:07:18.775671+00:00 | "data:\n batch_size: 128\n downstream_sequence: ''\n num_workers: 2\n pin_memory: true\n sequen(...TRUNCATED) | 0.107927 | 0.944307 | 136 | 0.891609 | 0.944269 | 0 | 0.044585 | 0.919695 | null | null | 0.017863 | 0.044585 | 0.223948 | 0.797521 | 0 | 2.925217 | 2.925217 | "[{\"epoch\": 0, \"train_loss\": 0.9668213725090027, \"val_loss\": 0.8897253130651583, \"val_pearson(...TRUNCATED) | https://wandb.ai/arushml/FactorizedNBM/runs/smbhqb2l | "/scratch/abr10036/projects/2025-interactions/results/20260710_firstorder_finegrid/20260710_firstord(...TRUNCATED) |
End of preview. Expand in Data Studio
fnbm-current-sweep-results
Grid-sweep trial results for fnbm-current.
Dataset Info
- Rows: 23
- Columns: 29
Columns
| Column | Type | Description |
|---|---|---|
| trial_id | Value('string') | Unique id for this trial: {sweep_name}__{combo_name} |
| experiment_name | Value('string') | Experiment folder slug this trial belongs to, e.g. fnbm-current |
| sweep_name | Value('string') | Base run name for the whole sweep (config['run']['name'] before per-combo suffixing) |
| combo_name | Value('string') | Per-combo run name (base name + swept param values) |
| grid_overrides | Value('string') | JSON-encoded {dot.path: value} of just the swept parameters for this trial |
| job_id | Value('string') | Cluster job id, if known |
| cluster | Value('string') | Cluster name, if known |
| timestamp | Value('string') | ISO 8601 UTC time this record was built |
| config_yaml | Value('string') | Full resolved config for this trial (reproducibility source of truth) |
| best_val_loss | Value('float64') | Best validation loss achieved during training |
| best_val_pearson_r | Value('float64') | Validation Pearson r at the best-val-loss epoch |
| best_epoch | Value('int64') | Epoch index of the best validation loss |
| sim_r2 | Value('float64') | Final-epoch R^2 against simulation ground truth |
| sim_pearson_r | Value('float64') | Final-epoch Pearson r against simulation ground truth |
| sim_mean_gt_z_abs_ratio | Value('float64') | Ground-truth mean fraction of |
| sim_mean_model_z_abs_ratio | Value('float64') | Model's mean fraction of |
| sim_z_abs_1_corr | Value('float64') | Correlation between model and ground-truth per-sample first-order |
| sim_z_abs_2_corr | Value('float64') | Correlation between model and ground-truth per-sample second-order |
| sim_z_abs_ratio_corr | Value('float64') | Correlation between model and ground-truth per-sample z_abs_ratio |
| sim_z_abs_ratio_mse | Value('float64') | MSE between model and ground-truth per-sample z_abs_ratio |
| absorption_gap | Value('float64') | sim_mean_model_z_abs_ratio - sim_mean_gt_z_abs_ratio (signed; >0 = over-attributes to second order) |
| promiscuity_mean_entropy | Value('float64') | Mean per-filter normalized positional entropy (diffuse activation proxy) |
| promiscuity_max_entropy | Value('float64') | Max per-filter normalized positional entropy |
| n_true_interaction_pairs | Value('float64') | Ground truth: number of true interacting motif pairs in the simulation (from sim_config.json) |
| interaction_effective_num_pairs | Value('float64') | Effective number of filter pairs carrying interaction mass (entropy-based) |
| interaction_concentration_gap | Value('float64') | interaction_effective_num_pairs - n_true_interaction_pairs |
| epoch_history | Value('string') | JSON-encoded list of per-epoch metrics.csv rows for this trial |
| wandb_run_url | Value('string') | Live wandb run URL for this trial, if wandb was enabled |
| report_pdf_path | Value('string') | Cluster-local path to this trial's latest simulation_eval report.pdf, if any |
Generation Parameters
{
"script_name": "sync_sweep_results.py",
"model": "fnbm-current",
"description": "Grid-sweep trial results for fnbm-current.",
"experiment_name": "fnbm-current",
"experiment_id": "fnbm-current",
"visualizer_type": "table",
"artifact_type": "eval_result",
"hyperparameters": {},
"input_datasets": []
}
Usage
from datasets import load_dataset
dataset = load_dataset("arushram/fnbm-current-sweep-results", split="train")
print(f"Loaded {len(dataset)} rows")
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