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Abstractor (Pre-Trained; reshuffled objects)
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Tags
train size = 3000; trial = 9
Notes
Author
awni00State
Finished
Start time
May 27th, 2023 6:42:15 AM
Runtime
35s
Tracked hours
31s
Run path
abstractor/object_argsort_autoregressive/kc1gi5sf
OS
Linux-4.18.0-425.13.1.el8_7.x86_64-x86_64-with-glibc2.28
Python version
3.10.8
Git repository
git clone https://github.com/jdlafferty/relational
Git state
git checkout -b "train-size-=-3000;-trial-=-9" b98437cbc7c2f1a78bfd13943d733bfd7fea87c5
Command
/diskarray/home/awni/projects/relational/experiments/object_argsort_autoregressive/evaluate_argsort_model_learning_curves.py --model abstractor --pretraining_mode pretraining --init_trainable True --pretraining_task_type "reshuffled objects" --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 500 --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 | 20 |
| Logical CPU count | 20 |
| GPU count | 1 |
| GPU type | NVIDIA GeForce RTX 4090 |
W&B CLI Version
0.15.3
Config
Config parameters are your model's inputs. Learn more
- {} 3 keys▶
- "Abstractor (Pre-Trained; reshuffled objects)"
- 3,000
- 9
Summary
Summary metrics are your model's outputs. Learn more
- {} 10 keys▶
- "table-file"
- 0.999895
- 102
- 0.0010000000474974513
- 0.023468010127544403
- 0.9929333329200744
- 0.0003825004096142948
- 0.9999799728393556
- 0.99965
- 0.9999650120735168
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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Name
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