Reversed_32 | ReAct Logs – Weights & Biases

Neel's group workspace

Group: Reversed_32

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Timestamps visible

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Val accuracy: {10: 2.299999952316284, 15: 60.20000076293945, 20: 62.79999923706055, 25: 59.880001068115234, 30: 57.560001373291016, 35: 56.15999984741211, 40: 55.18000030517578, 45: 54.52000045776367}

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Test accuracy (hard data): {10: 0.0, 15: 0.0, 20: 0.6399999856948853, 25: 1.159999966621399, 30: 1.399999976158142, 35: 1.100000023841858, 40: 0.9599999785423279, 45: 0.8799999952316284}

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Saving model to: model_.pth

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Saving current state to /fsx/awesome/DPT/outputs/model_.pth

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Model weights saved in /fsx/awesome/DPT/outputs/model_.pth/pytorch_model.bin

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Optimizer state saved in /fsx/awesome/DPT/outputs/model_.pth/optimizer.bin

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Scheduler state saved in /fsx/awesome/DPT/outputs/model_.pth/scheduler.bin

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Random states saved in /fsx/awesome/DPT/outputs/model_.pth/random_states_0.pkl

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Saving the state of AcceleratedScheduler to /fsx/awesome/DPT/outputs/model_.pth/custom_checkpoint_0.pkl

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Saving the state of AcceleratedOptimizer to /fsx/awesome/DPT/outputs/model_.pth/custom_checkpoint_1.pkl

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: Saving the state of DistributedDataParallel to /fsx/awesome/DPT/outputs/model_.pth/custom_checkpoint_2.pkl

2023-07-22 08:42:06

[07/22/2023 08:42:05 INFO]: OrderedDict([('max_iters', 15), ('run_id', 'hardwood-Anastacia'), ('test_acc', {10: 0.0, 15: 0.0, 20: 0.6399999856948853, 25: 1.159999966621399, 30: 1.399999976158142, 35: 1.100000023841858, 40: 0.9599999785423279, 45: 0.8799999952316284}), ('test_data', 5000), ('test_iters', [10, 15, 20, 25, 30, 35, 40, 45]), ('test_mode', 'default'), ('train_data', 50000), ('train_acc', {10: 96.01924896240234, 15: 99.98992919921875, 20: 99.98992919921875, 25: 99.98590850830078, 30: 99.98188018798828, 35: 99.97180938720703, 40: 99.96174621582031, 45: 99.96174621582031}), ('val_acc', {10: 2.299999952316284, 15: 60.20000076293945, 20: 62.79999923706055, 25: 59.880001068115234, 30: 57.560001373291016, 35: 56.15999984741211, 40: 55.18000030517578, 45: 54.52000045776367})])