ceb-sre

Jangerit's group workspace

Group: sweep_9xt0sw

1-20

of 46

Tags

PyG

Regressed

pretrained

Author

marcosfelt

State

Finished

Start time

March 15th, 2023 12:58:29 AM

Runtime

5m 58s

Tracked hours

5m 13s

Run path

ceb-sre/dl4thermo/2ezyj3qv

Linux-4.4.0-184-generic-x86_64-with-glibc2.34

Python version

3.8.16

Git repository

git clone https://marcosfelt:@git.rwth-aachen.de/jan.rittig/dl4thermo.git

Git state

git checkout -b "worthy-frog-1664" cba88990f7ee27fd2bf76b2bb93073518b5d89af

Command

/home/kcmf2/.cache/pypoetry/virtualenvs/dl4thermo-LHsi5UlR-py3.8/bin/kedro run --config conf/local/sweeps/sweep_9xt0sw/trial_45.yml

System Hardware

CPU count

W&B CLI Version

0.12.21

Group

sweep_9xt0sw

Config parameters are your model's inputs. Learn more

▶
Config parameters:{} 49 keys
- activation:
  "LeakyReLU"
- ▶
  associating_columns:[] 1 item
  - 0:
    "epsilonAB"
- auto_lr_find:
  false
- balanced_associating_sampling:
  true
- batch_size:
  500
- checkpoint_name:
  "model.ckpt"
- conv_type:
  "GINEConv"
- data_source:
  "regressed"
- dim_fingerprint:
  200
- dropout:
  0.3023267241186252
- early_stopping:
  false
- epochs:
  1,000
- explicit_hydrogen:
  false
- filter_non_associating:
  false
- filter_non_associating_inside_loss:
  true
- freeze_encoder:
  true
- freeze_normalization:
  true
- log_all_models:
  false
- lr:
  0.00005024858273847328
- ▶
  metrics:[] 3 items
  - 0:
    "mae"
  - 1:
    "mse"
  - 2:
    "r2"
- model_type:
  "GNN"
- multi_gru:
  false
- num_convs:
  2
- num_workers:
  0
- optimizer:
  "adam"
- optimizer_kwargs/beta_1:
  0.8402272140250656
- overwrite_save_dir:
  true
- pool_type:
  "add"
- save_dir:
  "data/07_model_output/sweep_9xt0sw/trial_45"
- scheduler:
  "noam"
- scheduler_kwargs/final_lr:
  0.00001
- scheduler_kwargs/final_lr_ratio:
  0.8760789534908556
- scheduler_kwargs/max_lr_ratio:
  68.16736364686093
- scheduler_kwargs/warmup_epochs:
  45
- separate_heads:
  false
- share_conv:
  false
- ▶
  smiles_columns:[] 1 item
  - 0:
    "smiles_1"
- ▶
  target_columns:[] 4 items
  - 0:
    "m"
  - 1:
    "sigma"
  - 2:
    "epsilon_k"
  - 3:
    "epsilonAB"
- target_weights:
  null
- targets_transformation:
  null
- use_dropout:
  false
- use_gru:
  true
- use_pretrained_model:
  false
- wandb_artifact_name:
  "pyg"
- wandb_checkpoint_artifact_id:
  "ceb-sre/dl4thermo/model-bili56s2:v3"
- wandb_entity:
  "ceb-sre"
- wandb_kwargs/group:
  "sweep_9xt0sw"
- wandb_project:
  "dl4thermo"
- ▶
  wandb_tags:[] 3 items
  - 0:
    "PyG"
  - 1:
    "Regressed"
  - 2:
    "pretrained"

Summary metrics are your model's outputs. Learn more

▶
Summary metrics:{} 87 keys
- epoch:
  999
- ▶
  graph_0:{} 4 keys
  - _type:
    "graph-file"
  - path:
    "media/graph/graph_0_summary_24bb4bf515504c8ce2aa.graph.json"
  - sha256:
    "24bb4bf515504c8ce2aa416e737fd418bf825f51e472bec28d26a092d2e64e5a"
  - size:
    3,269
- lr:
  0.00004402172577992034
- lr-Adam:
  0.00004402172577992034
- ▶
  parity_plot:{} 7 keys
- test_epsilon_k_mae:
  14.005507469177246
- test_epsilon_k_mse:
  378.4514465332031
- test_epsilon_k_r2:
  0.867815930743204
- test_epsilon_k_rmse:
  19.453828582908898
- test_epsilon_k_table:
  "table-file"
- test_epsilonAB_mae:
  61.79557037353515
- test_epsilonAB_mse:
  19,703.765625
- test_epsilonAB_r2:
  0.9885628057279704
- test_epsilonAB_rmse:
  140.37010231883426
- test_epsilonAB_table:
  "table-file"
- test_m_mae:
  0.19061800837516785
- test_m_mse:
  0.060792334377765656
- test_m_r2:
  0.9261836025828354
- test_m_rmse:
  0.24656101552712192
- test_m_table:
  "table-file"
- ▶
  test_parity_plot:{} 7 keys
- test_sigma_mae:
  0.05415623262524605
- test_sigma_mse:
  0.005224017892032862
- test_sigma_r2:
  0.9398541080504016
- test_sigma_rmse:
  0.07227736777188874
- test_sigma_table:
  "table-file"
- test_table:
  "table-file"
- time_per_step:
  0.12728358805179596
- total_test_mae:
  61.79557037353515
- total_test_mse:
  19,703.765625
- total_test_r2:
  0.9885628057279704
- total_test_rmse:
  140.37010231883426
- total_train_mae:
  43.91370391845703
- total_train_mse:
  28,890.6484375
- total_train_r2:
  0.964809669376033
- total_train_rmse:
  169.97249317904354
- total_val_mae:
  228.01687622070312
- total_val_mse:
  422,783.96875
- total_val_r2:
  0.741100116520119
- total_val_rmse:
  650.2184008085284
- train_epsilon_k_mae:
  21.220027923583984
- train_epsilon_k_mse:
  2,091.97265625
- train_epsilon_k_r2:
  0.5648184160080978
- train_epsilon_k_rmse:
  45.73808758846395
- train_epsilon_k_table:
  "table-file"
- train_epsilonAB_mae:
  43.91370391845703
- val_sigma_r2:
  0.4685534466218423
- val_sigma_rmse:
  0.2435489809886577
- val_sigma_table:
  "table-file"
- val_table:
  "table-file"

This run consumed these artifacts as inputs. Learn more

model

model-bili56s2:v3

This run produced these artifacts as outputs. Total: 6. Learn more

run-2ezyj3qv-train_table:v0

run_table

run-2ezyj3qv-val_table:v0

run_table

run-2ezyj3qv-test_table:v0

wandb-history

run-2ezyj3qv-history:v0