Awni00's group workspace
Simple Abstractor (Pre-Trained; reshuffled attr)
What makes this group special?
Tags
train size = 3000; trial = 9
Notes
Author
awni00State
Finished
Start time
May 3rd, 2023 9:56:03 AM
Runtime
36s
Tracked hours
32s
Run path
abstractor/object_argsort_autoregressive/cps424rk
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-=-3000;-trial-=-9" f397b06952b125c267dcbb3ea837aa1fcf1d84fd
Command
evaluate_argsort_model_learning_curves.py --model simple-abstractor --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 400 --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 2080 Ti |
W&B CLI Version
0.13.9
Config
Config parameters are your model's inputs. Learn more
- {} 3 keys▶
- "Simple Abstractor (Pre-Trained; reshuffled attr)"
- 3,000
- 9
Summary
Summary metrics are your model's outputs. Learn more
- {} 10 keys▶
- "table-file"
- 0.999345
- 91
- 0.0010000000474974513
- 0.02677299827337265
- 0.991166651248932
- 0.00039885996375232935
- 0.999970018863678
- 0.9991
- 0.9999300241470336
Artifact Inputs
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Artifact Outputs
This run produced these artifacts as outputs. Total: 2. Learn more
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