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Relational Abstractor (Pre-Trained; reshuffled attr)
What makes this group special?
Tags
train size = 1600; trial = 5
Notes
Author
State
Finished
Start time
April 29th, 2023 4:58:22 AM
Runtime
5m 37s
Tracked hours
3m 32s
Run path
abstractor/object_argsort_autoregressive/nzhzenqm
OS
Linux-3.10.0-1160.80.1.el7.x86_64-x86_64-with-glibc2.10
Python version
3.8.16
Git repository
git clone https://github.com/jdlafferty/relational
Git state
git checkout -b "train-size-=-1600;-trial-=-5" 753e3703eaa4d9005dad1d175c5d58791276f3b4
Command
evaluate_argsort_model_learning_curves.py --model rel-abstracter --pretraining_mode pretraining --init_trainable True --pretraining_task_type "reshuffled attr" --pretraining_task_data_path object_sorting_datasets/product_structure_reshuffled_object_sort_dataset.npy --eval_task_data_path object_sorting_datasets/product_structure_object_sort_dataset.npy --n_epochs 200 --early_stopping True --min_train_size 100 --max_train_size 3000 --train_size_step 100 --num_trials 10 --start_trial 0 --pretraining_train_size 1000 --wandb_project_name object_argsort_autoregressive
System Hardware
| CPU count | 36 |
| Logical CPU count | 36 |
| GPU count | 1 |
| GPU type | NVIDIA GeForce RTX 3090 |
W&B CLI Version
0.13.9
Config
Config parameters are your model's inputs. Learn more
- {} 3 keys▶
- "Relational Abstractor (Pre-Trained; reshuffled attr)"
- 1,600
- 5
Summary
Summary metrics are your model's outputs. Learn more
- {} 10 keys▶
- "table-file"
- 0.999955
- 87
- 0.0010000000474974513
- 0.019911792129278183
- 0.9938750267028807
- 0.000309187569655478
- 0.999970018863678
- 0.99995
- 0.9999866485595704
Artifact Inputs
This run consumed these artifacts as inputs. Learn more
Artifact Outputs
This run produced these artifacts as outputs. Total: 2. Learn more
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