Add report for hyper-parameter optimization
This commit is contained in:
parent
db2b7d973c
commit
b7057ff456
@ -1,139 +1,139 @@
|
|||||||
,summary,config,name
|
,summary,config,name
|
||||||
0,"{'test/epoch_loss': 0.5664619127909343, 'train/epoch_acc': 0.8230958230958231, 'train/batch_loss': 0.33577921986579895, 'epoch': 9, '_wandb': {'runtime': 363}, '_timestamp': 1680692970.2016854, 'test/recall': 0.6170212765957447, 'test/precision': 0.8285714285714286, '_step': 2059, '_runtime': 367.13677954673767, 'test/f1-score': 0.7073170731707318, 'test/epoch_acc': 0.7333333333333334, 'train/epoch_loss': 0.4241055610431793}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0003}",fiery-sweep-26
|
0,"{'test/epoch_acc': 0.7333333333333334, 'test/precision': 0.8285714285714286, 'test/epoch_loss': 0.5664619127909343, 'train/epoch_acc': 0.8230958230958231, '_step': 2059, 'epoch': 9, '_timestamp': 1680692970.2016854, 'test/f1-score': 0.7073170731707318, 'train/batch_loss': 0.33577921986579895, 'train/epoch_loss': 0.4241055610431793, '_wandb': {'runtime': 363}, '_runtime': 367.13677954673767, 'test/recall': 0.6170212765957447}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0003}",fiery-sweep-26
|
||||||
1,"{'test/recall': 0.8222222222222222, 'test/precision': 0.6851851851851852, '_runtime': 341.8420207500458, '_timestamp': 1680692589.503975, '_wandb': {'runtime': 338}, 'test/f1-score': 0.7474747474747475, 'test/epoch_acc': 0.7222222222222222, 'test/epoch_loss': 0.6454579922888014, 'train/epoch_acc': 0.7125307125307125, 'train/batch_loss': 0.7014500498771667, '_step': 1039, 'epoch': 9, 'train/epoch_loss': 0.649790015355375}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0003}",radiant-sweep-25
|
1,"{'epoch': 9, '_wandb': {'runtime': 338}, '_runtime': 341.8420207500458, 'test/precision': 0.6851851851851852, 'train/epoch_acc': 0.7125307125307125, 'train/epoch_loss': 0.649790015355375, '_step': 1039, 'test/recall': 0.8222222222222222, 'test/f1-score': 0.7474747474747475, 'test/epoch_acc': 0.7222222222222222, 'test/epoch_loss': 0.6454579922888014, 'train/batch_loss': 0.7014500498771667, '_timestamp': 1680692589.503975}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0003}",radiant-sweep-25
|
||||||
2,"{'test/recall': 0.7837837837837838, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.935483870967742, 'train/batch_loss': 0.01956617273390293, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 333}, '_runtime': 336.8275649547577, 'train/epoch_loss': 0.01614290558709019, '_timestamp': 1680692234.39516, 'test/f1-score': 0.8529411764705881, 'test/epoch_loss': 0.34812947780333664, 'train/epoch_acc': 0.9987714987714988}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",blooming-sweep-24
|
2,"{'test/recall': 0.7837837837837838, 'test/precision': 0.935483870967742, 'test/epoch_loss': 0.34812947780333664, 'train/epoch_loss': 0.01614290558709019, '_step': 1039, 'epoch': 9, '_timestamp': 1680692234.39516, 'test/epoch_acc': 0.888888888888889, 'train/epoch_acc': 0.9987714987714988, 'train/batch_loss': 0.01956617273390293, '_wandb': {'runtime': 333}, '_runtime': 336.8275649547577, 'test/f1-score': 0.8529411764705881}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",blooming-sweep-24
|
||||||
3,"{'test/epoch_acc': 0.8, 'train/batch_loss': 0.5222326517105103, 'train/epoch_loss': 0.5324229019572753, 'epoch': 9, '_wandb': {'runtime': 327}, '_runtime': 331.57809829711914, 'test/f1-score': 0.7954545454545455, 'test/epoch_loss': 0.5553177932898203, 'train/epoch_acc': 0.8353808353808354, '_step': 529, '_timestamp': 1680691883.3877182, 'test/recall': 0.8333333333333334, 'test/precision': 0.7608695652173914}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0003}",visionary-sweep-23
|
3,"{'_wandb': {'runtime': 327}, '_runtime': 331.57809829711914, '_timestamp': 1680691883.3877182, 'test/precision': 0.7608695652173914, 'test/epoch_loss': 0.5553177932898203, 'train/batch_loss': 0.5222326517105103, 'train/epoch_loss': 0.5324229019572753, 'epoch': 9, 'test/recall': 0.8333333333333334, 'test/f1-score': 0.7954545454545455, 'test/epoch_acc': 0.8, 'train/epoch_acc': 0.8353808353808354, '_step': 529}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0003}",visionary-sweep-23
|
||||||
4,"{'test/f1-score': 0.7076923076923076, 'train/epoch_acc': 0.5577395577395577, '_step': 410, 'epoch': 1, 'test/recall': 0.8846153846153846, 'test/epoch_acc': 0.5777777777777778, 'test/precision': 0.5897435897435898, 'test/epoch_loss': 1.5602711306677923, 'train/batch_loss': 0.5083656311035156, 'train/epoch_loss': 0.7508098256090057, '_wandb': {'runtime': 70}, '_runtime': 71.64615154266357, '_timestamp': 1680691538.7247725}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",ancient-sweep-22
|
4,"{'train/epoch_loss': 0.7508098256090057, 'epoch': 1, '_timestamp': 1680691538.7247725, 'test/recall': 0.8846153846153846, 'test/epoch_acc': 0.5777777777777778, 'train/epoch_acc': 0.5577395577395577, 'train/batch_loss': 0.5083656311035156, '_step': 410, '_wandb': {'runtime': 70}, '_runtime': 71.64615154266357, 'test/f1-score': 0.7076923076923076, 'test/precision': 0.5897435897435898, 'test/epoch_loss': 1.5602711306677923}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",ancient-sweep-22
|
||||||
5,"{'test/precision': 0.6885245901639344, 'test/epoch_loss': 0.4844042791260613, 'train/epoch_loss': 0.49390909720111537, '_step': 529, 'epoch': 9, '_timestamp': 1680691453.5148375, 'test/f1-score': 0.8, 'test/epoch_acc': 0.7666666666666667, 'train/epoch_acc': 0.769041769041769, 'train/batch_loss': 0.4559023082256317, '_wandb': {'runtime': 328}, '_runtime': 331.44886469841003, 'test/recall': 0.9545454545454546}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.003}",fresh-sweep-22
|
5,"{'_step': 529, 'epoch': 9, '_wandb': {'runtime': 328}, '_timestamp': 1680691453.5148375, 'test/precision': 0.6885245901639344, 'train/epoch_loss': 0.49390909720111537, '_runtime': 331.44886469841003, 'test/recall': 0.9545454545454546, 'test/f1-score': 0.8, 'test/epoch_acc': 0.7666666666666667, 'test/epoch_loss': 0.4844042791260613, 'train/epoch_acc': 0.769041769041769, 'train/batch_loss': 0.4559023082256317}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.003}",fresh-sweep-22
|
||||||
6,"{'test/epoch_loss': 0.26263883135527266, 'train/epoch_acc': 0.9975429975429976, 'train/batch_loss': 0.0031523401848971844, 'train/epoch_loss': 0.018423480946079804, '_wandb': {'runtime': 355}, '_runtime': 358.66950702667236, '_timestamp': 1680691110.042932, 'test/recall': 0.8867924528301887, 'test/f1-score': 0.9306930693069309, 'test/epoch_acc': 0.9222222222222224, 'test/precision': 0.9791666666666666, '_step': 2059, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.01}",pleasant-sweep-21
|
6,"{'test/epoch_acc': 0.9222222222222224, 'test/epoch_loss': 0.26263883135527266, 'train/epoch_acc': 0.9975429975429976, 'epoch': 9, '_wandb': {'runtime': 355}, '_timestamp': 1680691110.042932, 'test/recall': 0.8867924528301887, 'test/f1-score': 0.9306930693069309, '_step': 2059, '_runtime': 358.66950702667236, 'test/precision': 0.9791666666666666, 'train/batch_loss': 0.0031523401848971844, 'train/epoch_loss': 0.018423480946079804}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.01}",pleasant-sweep-21
|
||||||
7,"{'train/batch_loss': 0.003317732596769929, 'epoch': 9, '_wandb': {'runtime': 329}, '_runtime': 332.6156196594238, 'test/f1-score': 0.8865979381443299, 'test/epoch_loss': 0.3669874522421095, 'train/epoch_acc': 1, 'train/epoch_loss': 0.0014873178028192654, '_step': 279, '_timestamp': 1680690741.3215847, 'test/recall': 0.9148936170212766, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.86}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.01}",fragrant-sweep-20
|
7,"{'train/epoch_loss': 0.0014873178028192654, 'epoch': 9, '_runtime': 332.6156196594238, 'test/recall': 0.9148936170212766, 'test/f1-score': 0.8865979381443299, 'test/epoch_acc': 0.8777777777777778, 'test/epoch_loss': 0.3669874522421095, 'train/batch_loss': 0.003317732596769929, '_step': 279, '_wandb': {'runtime': 329}, '_timestamp': 1680690741.3215847, 'test/precision': 0.86, 'train/epoch_acc': 1}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.01}",fragrant-sweep-20
|
||||||
8,"{'test/recall': 0.82, 'test/precision': 0.7592592592592593, 'test/epoch_loss': 0.5786970999505785, 'train/epoch_acc': 0.8206388206388207, '_step': 149, 'epoch': 9, '_runtime': 342.05230498313904, 'test/epoch_acc': 0.7555555555555555, 'train/batch_loss': 0.58731609582901, 'train/epoch_loss': 0.5623220165765842, '_wandb': {'runtime': 338}, '_timestamp': 1680690397.165603, 'test/f1-score': 0.7884615384615384}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",treasured-sweep-19
|
8,"{'epoch': 9, 'test/recall': 0.82, 'test/precision': 0.7592592592592593, 'test/epoch_loss': 0.5786970999505785, 'train/epoch_acc': 0.8206388206388207, 'train/batch_loss': 0.58731609582901, '_step': 149, '_runtime': 342.05230498313904, '_timestamp': 1680690397.165603, 'test/f1-score': 0.7884615384615384, 'test/epoch_acc': 0.7555555555555555, 'train/epoch_loss': 0.5623220165765842, '_wandb': {'runtime': 338}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",treasured-sweep-19
|
||||||
9,"{'test/precision': 0.8536585365853658, 'test/epoch_loss': 0.6037532766660054, 'train/epoch_acc': 0.7788697788697788, 'epoch': 9, '_wandb': {'runtime': 357}, '_runtime': 360.5366156101227, 'test/f1-score': 0.7865168539325843, 'test/epoch_acc': 0.788888888888889, 'train/batch_loss': 0.5736206769943237, '_step': 2059, '_timestamp': 1680690042.488695, 'test/recall': 0.7291666666666666, 'train/epoch_loss': 0.5984062318134074}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.0001}",desert-sweep-18
|
9,"{'_timestamp': 1680690042.488695, 'test/f1-score': 0.7865168539325843, 'test/precision': 0.8536585365853658, 'train/batch_loss': 0.5736206769943237, 'epoch': 9, '_wandb': {'runtime': 357}, '_runtime': 360.5366156101227, 'test/epoch_loss': 0.6037532766660054, 'train/epoch_acc': 0.7788697788697788, 'train/epoch_loss': 0.5984062318134074, '_step': 2059, 'test/recall': 0.7291666666666666, 'test/epoch_acc': 0.788888888888889}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.0001}",desert-sweep-18
|
||||||
10,"{'_wandb': {'runtime': 362}, '_runtime': 365.3367943763733, '_timestamp': 1680689670.8310964, 'test/f1-score': 0.8333333333333334, 'test/precision': 0.945945945945946, 'train/epoch_loss': 0.3086323318522451, '_step': 2059, 'epoch': 9, 'test/recall': 0.7446808510638298, 'test/epoch_acc': 0.8444444444444444, 'test/epoch_loss': 0.3740654948684904, 'train/epoch_acc': 0.8697788697788698, 'train/batch_loss': 0.5778521299362183}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.003}",celestial-sweep-17
|
10,"{'_timestamp': 1680689670.8310964, 'test/f1-score': 0.8333333333333334, 'test/epoch_loss': 0.3740654948684904, 'train/epoch_acc': 0.8697788697788698, '_step': 2059, 'epoch': 9, 'test/recall': 0.7446808510638298, 'test/epoch_acc': 0.8444444444444444, 'test/precision': 0.945945945945946, 'train/batch_loss': 0.5778521299362183, 'train/epoch_loss': 0.3086323318522451, '_wandb': {'runtime': 362}, '_runtime': 365.3367943763733}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.003}",celestial-sweep-17
|
||||||
11,"{'train/epoch_acc': 1, 'train/batch_loss': 0.004256190732121468, '_step': 149, '_runtime': 340.39124369621277, '_timestamp': 1680689237.7951498, 'test/precision': 0.9069767441860463, 'test/epoch_loss': 0.18080708616309696, 'train/epoch_loss': 0.0053219743558098115, 'epoch': 9, '_wandb': {'runtime': 337}, 'test/recall': 0.9285714285714286, 'test/f1-score': 0.9176470588235294, 'test/epoch_acc': 0.9222222222222224}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.01}",cosmic-sweep-15
|
11,"{'test/recall': 0.9285714285714286, 'test/f1-score': 0.9176470588235294, 'test/precision': 0.9069767441860463, 'train/epoch_acc': 1, 'epoch': 9, '_wandb': {'runtime': 337}, '_runtime': 340.39124369621277, '_timestamp': 1680689237.7951498, 'train/epoch_loss': 0.0053219743558098115, '_step': 149, 'test/epoch_acc': 0.9222222222222224, 'test/epoch_loss': 0.18080708616309696, 'train/batch_loss': 0.004256190732121468}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.01}",cosmic-sweep-15
|
||||||
12,"{'_step': 2059, '_runtime': 359.0396990776062, '_timestamp': 1680688886.363035, 'test/recall': 0.8222222222222222, 'test/f1-score': 0.8705882352941177, 'test/precision': 0.925, 'train/batch_loss': 0.21692615747451785, 'epoch': 9, '_wandb': {'runtime': 356}, 'test/epoch_acc': 0.8777777777777778, 'test/epoch_loss': 0.23811448697621623, 'train/epoch_acc': 0.968058968058968, 'train/epoch_loss': 0.09628425111664636}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.001}",stilted-sweep-14
|
12,"{'_timestamp': 1680688886.363035, 'test/recall': 0.8222222222222222, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.925, 'train/epoch_loss': 0.09628425111664636, 'test/epoch_loss': 0.23811448697621623, 'train/epoch_acc': 0.968058968058968, 'train/batch_loss': 0.21692615747451785, '_step': 2059, 'epoch': 9, '_wandb': {'runtime': 356}, '_runtime': 359.0396990776062, 'test/f1-score': 0.8705882352941177}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.001}",stilted-sweep-14
|
||||||
13,"{'epoch': 9, '_runtime': 336.5640392303467, '_timestamp': 1680688517.0028613, 'test/recall': 0.9, 'test/precision': 0.9574468085106383, 'train/epoch_acc': 1, 'train/batch_loss': 0.007201554253697395, 'train/epoch_loss': 0.007631345846546077, '_step': 149, '_wandb': {'runtime': 333}, 'test/f1-score': 0.9278350515463918, 'test/epoch_acc': 0.9222222222222224, 'test/epoch_loss': 0.16714997291564945}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",frosty-sweep-13
|
13,"{'_step': 149, 'test/f1-score': 0.9278350515463918, 'test/epoch_loss': 0.16714997291564945, 'train/epoch_acc': 1, 'test/epoch_acc': 0.9222222222222224, 'test/precision': 0.9574468085106383, 'train/batch_loss': 0.007201554253697395, 'epoch': 9, '_wandb': {'runtime': 333}, '_runtime': 336.5640392303467, '_timestamp': 1680688517.0028613, 'test/recall': 0.9, 'train/epoch_loss': 0.007631345846546077}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",frosty-sweep-13
|
||||||
14,"{'test/f1-score': 0.8674698795180724, 'test/precision': 0.9230769230769232, 'train/batch_loss': 0.27152174711227417, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 328}, 'test/epoch_acc': 0.8777777777777778, 'test/epoch_loss': 0.32556109494633145, 'train/epoch_acc': 0.9496314496314496, 'train/epoch_loss': 0.17368088453934877, '_runtime': 331.98337984085083, '_timestamp': 1680688162.2054858, 'test/recall': 0.8181818181818182}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",young-sweep-12
|
14,"{'test/epoch_acc': 0.8777777777777778, 'test/epoch_loss': 0.32556109494633145, 'train/epoch_loss': 0.17368088453934877, '_runtime': 331.98337984085083, '_timestamp': 1680688162.2054858, 'test/recall': 0.8181818181818182, 'test/f1-score': 0.8674698795180724, 'test/precision': 0.9230769230769232, 'train/epoch_acc': 0.9496314496314496, 'train/batch_loss': 0.27152174711227417, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 328}}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",young-sweep-12
|
||||||
15,"{'test/recall': 0.8292682926829268, 'test/epoch_acc': 0.7222222222222222, 'test/epoch_loss': 0.5193446947468652, 'train/batch_loss': 0.3307788372039795, '_wandb': {'runtime': 332}, '_timestamp': 1680687816.5057352, '_runtime': 335.6552822589874, 'test/f1-score': 0.7311827956989247, 'test/precision': 0.6538461538461539, 'train/epoch_acc': 0.7469287469287469, 'train/epoch_loss': 0.5277571982775039, '_step': 1039, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.1}",sandy-sweep-11
|
15,"{'_wandb': {'runtime': 332}, 'test/f1-score': 0.7311827956989247, 'train/epoch_loss': 0.5277571982775039, '_step': 1039, 'epoch': 9, 'test/recall': 0.8292682926829268, 'test/epoch_acc': 0.7222222222222222, 'test/precision': 0.6538461538461539, 'test/epoch_loss': 0.5193446947468652, 'train/epoch_acc': 0.7469287469287469, 'train/batch_loss': 0.3307788372039795, '_runtime': 335.6552822589874, '_timestamp': 1680687816.5057352}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.1}",sandy-sweep-11
|
||||||
16,"{'test/precision': 0.8085106382978723, 'epoch': 9, '_wandb': {'runtime': 334}, '_runtime': 336.80703043937683, 'test/recall': 0.9047619047619048, 'test/f1-score': 0.853932584269663, 'test/epoch_acc': 0.8555555555555556, '_step': 149, '_timestamp': 1680687470.9289024, 'test/epoch_loss': 0.4616309046745301, 'train/epoch_acc': 1, 'train/batch_loss': 0.0030224076472222805, 'train/epoch_loss': 0.003708146820279612}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",laced-sweep-10
|
16,"{'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.8085106382978723, 'test/epoch_loss': 0.4616309046745301, '_wandb': {'runtime': 334}, '_runtime': 336.80703043937683, '_timestamp': 1680687470.9289024, 'test/recall': 0.9047619047619048, 'train/batch_loss': 0.0030224076472222805, 'train/epoch_loss': 0.003708146820279612, '_step': 149, 'epoch': 9, 'test/f1-score': 0.853932584269663, 'train/epoch_acc': 1}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",laced-sweep-10
|
||||||
17,"{'_step': 422, 'epoch': 7, '_runtime': 265.48077392578125, '_timestamp': 1680687113.1220188, 'test/recall': 0.08888888888888889, 'test/f1-score': 0.14035087719298245, 'test/precision': 0.3333333333333333, 'test/epoch_loss': 11610.708938450283, 'train/batch_loss': 9.74098777770996, '_wandb': {'runtime': 265}, 'test/epoch_acc': 0.45555555555555555, 'train/epoch_acc': 0.5331695331695332, 'train/epoch_loss': 9.16968992828444}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",jumping-sweep-9
|
17,"{'_runtime': 265.48077392578125, 'test/recall': 0.08888888888888889, 'test/epoch_acc': 0.45555555555555555, 'train/epoch_loss': 9.16968992828444, '_wandb': {'runtime': 265}, 'epoch': 7, '_timestamp': 1680687113.1220188, 'test/f1-score': 0.14035087719298245, 'test/precision': 0.3333333333333333, 'test/epoch_loss': 11610.708938450283, 'train/epoch_acc': 0.5331695331695332, 'train/batch_loss': 9.74098777770996, '_step': 422}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",jumping-sweep-9
|
||||||
18,"{'test/recall': 0.803921568627451, 'test/f1-score': 0.845360824742268, 'test/epoch_acc': 0.8333333333333334, 'test/precision': 0.8913043478260869, 'test/epoch_loss': 0.3831123087141249, '_step': 529, '_runtime': 330.36346793174744, '_timestamp': 1680686834.80723, 'train/batch_loss': 0.34334877133369446, 'train/epoch_loss': 0.3055295220024756, 'epoch': 9, '_wandb': {'runtime': 327}, 'train/epoch_acc': 0.8955773955773956}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.0003}",dutiful-sweep-8
|
18,"{'test/precision': 0.8913043478260869, 'train/epoch_acc': 0.8955773955773956, 'train/epoch_loss': 0.3055295220024756, '_wandb': {'runtime': 327}, '_timestamp': 1680686834.80723, 'test/f1-score': 0.845360824742268, 'test/epoch_acc': 0.8333333333333334, 'test/epoch_loss': 0.3831123087141249, 'train/batch_loss': 0.34334877133369446, '_step': 529, 'epoch': 9, '_runtime': 330.36346793174744, 'test/recall': 0.803921568627451}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.0003}",dutiful-sweep-8
|
||||||
19,"{'train/epoch_acc': 0.484029484029484, 'train/epoch_loss': 'NaN', 'epoch': 2, '_wandb': {'runtime': 99}, '_runtime': 99.40804982185364, '_timestamp': 1680686491.634724, 'test/recall': 1, 'test/f1-score': 0.6259541984732825, '_step': 157, 'test/epoch_acc': 0.45555555555555555, 'test/precision': 0.45555555555555555, 'test/epoch_loss': 6.554853016439314e+29, 'train/batch_loss': 'NaN'}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",olive-sweep-7
|
19,"{'epoch': 2, '_runtime': 99.40804982185364, '_timestamp': 1680686491.634724, 'test/epoch_acc': 0.45555555555555555, 'test/precision': 0.45555555555555555, 'test/epoch_loss': 6.554853016439314e+29, 'train/batch_loss': 'NaN', '_step': 157, '_wandb': {'runtime': 99}, 'test/recall': 1, 'test/f1-score': 0.6259541984732825, 'train/epoch_acc': 0.484029484029484, 'train/epoch_loss': 'NaN'}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",olive-sweep-7
|
||||||
20,"{'_step': 279, '_timestamp': 1680686383.3591404, 'test/f1-score': 0.8695652173913044, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.851063829787234, 'train/batch_loss': 0.3707323968410492, 'epoch': 9, '_wandb': {'runtime': 334}, '_runtime': 337.17863941192627, 'test/recall': 0.8888888888888888, 'test/epoch_loss': 0.35141510632303025, 'train/epoch_acc': 0.9103194103194104, 'train/epoch_loss': 0.3219767680771521}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.001}",good-sweep-6
|
20,"{'_wandb': {'runtime': 334}, '_runtime': 337.17863941192627, 'test/recall': 0.8888888888888888, 'test/f1-score': 0.8695652173913044, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.851063829787234, 'test/epoch_loss': 0.35141510632303025, 'train/epoch_acc': 0.9103194103194104, 'train/batch_loss': 0.3707323968410492, '_step': 279, 'epoch': 9, '_timestamp': 1680686383.3591404, 'train/epoch_loss': 0.3219767680771521}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.001}",good-sweep-6
|
||||||
21,"{'test/f1-score': 0.6601941747572815, 'test/epoch_acc': 0.6111111111111112, 'test/precision': 0.6296296296296297, 'train/batch_loss': 0.7027227878570557, 'train/epoch_acc': 0.5196560196560196, '_step': 149, 'epoch': 9, '_wandb': {'runtime': 342}, '_runtime': 344.80718994140625, '_timestamp': 1680686028.304971, 'test/recall': 0.6938775510204082, 'test/epoch_loss': 0.6818753732575311, 'train/epoch_loss': 0.6907664721955246}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.0003}",summer-sweep-5
|
21,"{'test/recall': 0.6938775510204082, 'test/f1-score': 0.6601941747572815, 'test/epoch_acc': 0.6111111111111112, 'train/epoch_acc': 0.5196560196560196, '_wandb': {'runtime': 342}, '_runtime': 344.80718994140625, '_timestamp': 1680686028.304971, 'test/precision': 0.6296296296296297, 'test/epoch_loss': 0.6818753732575311, 'train/batch_loss': 0.7027227878570557, 'train/epoch_loss': 0.6907664721955246, '_step': 149, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.0003}",summer-sweep-5
|
||||||
22,"{'_step': 529, '_wandb': {'runtime': 331}, '_runtime': 333.9663326740265, '_timestamp': 1680685671.7387648, 'test/f1-score': 0.9066666666666668, 'test/epoch_acc': 0.9222222222222224, 'test/precision': 0.9444444444444444, 'train/epoch_acc': 0.9864864864864864, 'train/batch_loss': 0.15035715699195862, 'train/epoch_loss': 0.10497688309859292, 'epoch': 9, 'test/recall': 0.8717948717948718, 'test/epoch_loss': 0.22382020586066775}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.001}",firm-sweep-4
|
22,"{'epoch': 9, '_timestamp': 1680685671.7387648, 'test/epoch_acc': 0.9222222222222224, 'test/epoch_loss': 0.22382020586066775, 'train/epoch_acc': 0.9864864864864864, '_step': 529, '_runtime': 333.9663326740265, 'test/recall': 0.8717948717948718, 'test/f1-score': 0.9066666666666668, 'test/precision': 0.9444444444444444, 'train/batch_loss': 0.15035715699195862, 'train/epoch_loss': 0.10497688309859292, '_wandb': {'runtime': 331}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.001}",firm-sweep-4
|
||||||
23,"{'_step': 149, 'test/recall': 0.925, 'test/f1-score': 0.6379310344827587, 'train/epoch_loss': 0.6564877619028677, 'test/epoch_loss': 0.6597137530644734, 'train/epoch_acc': 0.5909090909090909, 'epoch': 9, '_wandb': {'runtime': 333}, '_runtime': 335.79468297958374, '_timestamp': 1680685319.453976, 'test/epoch_acc': 0.5333333333333333, 'test/precision': 0.4868421052631579, 'train/batch_loss': 0.652446985244751}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.0001}",genial-sweep-3
|
23,"{'_step': 149, '_runtime': 335.79468297958374, 'test/recall': 0.925, 'test/f1-score': 0.6379310344827587, 'test/precision': 0.4868421052631579, 'test/epoch_loss': 0.6597137530644734, 'train/batch_loss': 0.652446985244751, 'epoch': 9, '_wandb': {'runtime': 333}, '_timestamp': 1680685319.453976, 'test/epoch_acc': 0.5333333333333333, 'train/epoch_acc': 0.5909090909090909, 'train/epoch_loss': 0.6564877619028677}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.0001}",genial-sweep-3
|
||||||
24,"{'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.6271186440677966, 'test/epoch_loss': 0.5467572536733415, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 329}, '_runtime': 331.50625491142273, 'test/f1-score': 0.7628865979381443, '_timestamp': 1680684975.004809, 'test/recall': 0.9736842105263158, 'train/epoch_acc': 0.7899262899262899, 'train/batch_loss': 0.5583129525184631, 'train/epoch_loss': 0.4703364581675143}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.1}",fine-sweep-2
|
24,"{'_step': 529, 'test/recall': 0.9736842105263158, 'test/f1-score': 0.7628865979381443, 'test/precision': 0.6271186440677966, 'test/epoch_loss': 0.5467572536733415, 'train/epoch_acc': 0.7899262899262899, 'epoch': 9, '_wandb': {'runtime': 329}, '_runtime': 331.50625491142273, '_timestamp': 1680684975.004809, 'test/epoch_acc': 0.7444444444444445, 'train/batch_loss': 0.5583129525184631, 'train/epoch_loss': 0.4703364581675143}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.1}",fine-sweep-2
|
||||||
25,"{'test/epoch_acc': 0.9, 'train/epoch_acc': 0.9987714987714988, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 447}, '_runtime': 450.5545320510864, 'test/recall': 0.8863636363636364, 'train/epoch_loss': 0.007131033717467008, '_timestamp': 1680684633.811369, 'test/f1-score': 0.896551724137931, 'test/precision': 0.9069767441860463, 'test/epoch_loss': 0.30911533037821454, 'train/batch_loss': 0.005764181260019541}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.01}",visionary-sweep-1
|
25,"{'_timestamp': 1680684633.811369, 'test/f1-score': 0.896551724137931, 'test/epoch_acc': 0.9, 'test/epoch_loss': 0.30911533037821454, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 447}, '_runtime': 450.5545320510864, 'train/epoch_acc': 0.9987714987714988, 'train/batch_loss': 0.005764181260019541, 'test/recall': 0.8863636363636364, 'test/precision': 0.9069767441860463, 'train/epoch_loss': 0.007131033717467008}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.01}",visionary-sweep-1
|
||||||
26,"{'_wandb': {'runtime': 83}, '_timestamp': 1680629962.8990817, 'train/epoch_acc': 0.8931203931203932, 'train/epoch_loss': 0.2428556958016658, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.8444444444444444, 'test/epoch_loss': 0.29840316110187104, '_step': 239, 'epoch': 1, '_runtime': 83.58446168899536, 'test/recall': 0.9047619047619048, 'test/f1-score': 0.8735632183908046, 'train/batch_loss': 0.08615076541900635}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.1}",stoic-sweep-14
|
26,"{'_step': 239, 'epoch': 1, '_timestamp': 1680629962.8990817, 'train/epoch_acc': 0.8931203931203932, 'train/batch_loss': 0.08615076541900635, '_wandb': {'runtime': 83}, '_runtime': 83.58446168899536, 'test/recall': 0.9047619047619048, 'test/f1-score': 0.8735632183908046, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.8444444444444444, 'test/epoch_loss': 0.29840316110187104, 'train/epoch_loss': 0.2428556958016658}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.1}",stoic-sweep-14
|
||||||
27,"{'epoch': 9, '_wandb': {'runtime': 347}, '_runtime': 348.9410927295685, '_timestamp': 1680629872.8401277, 'test/recall': 0.975, 'test/f1-score': 0.951219512195122, 'test/epoch_acc': 0.9555555555555556, '_step': 149, 'train/batch_loss': 0.10338585078716278, 'train/epoch_loss': 0.1163152276517718, 'train/epoch_acc': 0.9803439803439804, 'test/epoch_loss': 0.20102048052681817, 'test/precision': 0.9285714285714286}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.01}",rich-sweep-13
|
27,"{'_timestamp': 1680629872.8401277, 'test/recall': 0.975, 'test/f1-score': 0.951219512195122, 'test/epoch_loss': 0.20102048052681817, 'train/epoch_acc': 0.9803439803439804, '_step': 149, '_wandb': {'runtime': 347}, '_runtime': 348.9410927295685, 'train/batch_loss': 0.10338585078716278, 'train/epoch_loss': 0.1163152276517718, 'epoch': 9, 'test/epoch_acc': 0.9555555555555556, 'test/precision': 0.9285714285714286}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.01}",rich-sweep-13
|
||||||
28,"{'train/batch_loss': 82027960, '_step': 210, 'epoch': 3, '_wandb': {'runtime': 135}, '_runtime': 132.22715950012207, '_timestamp': 1680629513.1781075, 'test/f1-score': 0.6721311475409836, 'test/epoch_acc': 0.5555555555555556, 'test/recall': 0.9111111111111112, 'test/precision': 0.5324675324675324, 'test/epoch_loss': 3.395405118153546e+20, 'train/epoch_acc': 0.5282555282555282, 'train/epoch_loss': 60563307.6520902}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.003}",smooth-sweep-12
|
28,"{'_timestamp': 1680629513.1781075, 'test/epoch_loss': 3.395405118153546e+20, 'train/batch_loss': 82027960, 'train/epoch_loss': 60563307.6520902, 'epoch': 3, '_wandb': {'runtime': 135}, '_runtime': 132.22715950012207, 'test/recall': 0.9111111111111112, 'test/f1-score': 0.6721311475409836, 'test/epoch_acc': 0.5555555555555556, 'test/precision': 0.5324675324675324, 'train/epoch_acc': 0.5282555282555282, '_step': 210}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.003}",smooth-sweep-12
|
||||||
29,"{'_wandb': {'runtime': 326}, 'test/recall': 0.8888888888888888, 'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.5245901639344263, 'train/batch_loss': 0.5836847424507141, 'train/epoch_loss': 0.6072891213970044, '_step': 279, 'epoch': 9, 'test/f1-score': 0.6597938144329897, 'test/epoch_loss': 0.6240786300765143, 'train/epoch_acc': 0.7469287469287469, '_runtime': 327.2181556224823, '_timestamp': 1680629374.0562296}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.0003}",resilient-sweep-11
|
29,"{'test/recall': 0.8888888888888888, 'test/f1-score': 0.6597938144329897, 'test/precision': 0.5245901639344263, 'test/epoch_loss': 0.6240786300765143, '_step': 279, '_runtime': 327.2181556224823, '_timestamp': 1680629374.0562296, 'test/epoch_acc': 0.6333333333333333, 'train/epoch_acc': 0.7469287469287469, 'train/batch_loss': 0.5836847424507141, 'train/epoch_loss': 0.6072891213970044, 'epoch': 9, '_wandb': {'runtime': 326}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.0003}",resilient-sweep-11
|
||||||
30,"{'train/epoch_acc': 0.9717444717444718, 'epoch': 9, 'test/f1-score': 0.8958333333333334, 'test/precision': 0.9772727272727272, 'test/epoch_loss': 0.2657569663392173, 'test/recall': 0.8269230769230769, 'test/epoch_acc': 0.888888888888889, 'train/batch_loss': 0.13025684654712677, 'train/epoch_loss': 0.12745249926751018, '_step': 529, '_wandb': {'runtime': 330}, '_runtime': 332.23273372650146, '_timestamp': 1680629038.456323}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",serene-sweep-10
|
30,"{'_wandb': {'runtime': 330}, '_timestamp': 1680629038.456323, 'test/epoch_loss': 0.2657569663392173, 'train/epoch_loss': 0.12745249926751018, '_step': 529, '_runtime': 332.23273372650146, 'test/recall': 0.8269230769230769, 'test/f1-score': 0.8958333333333334, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9772727272727272, 'train/epoch_acc': 0.9717444717444718, 'train/batch_loss': 0.13025684654712677, 'epoch': 9}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",serene-sweep-10
|
||||||
31,"{'_step': 1039, '_wandb': {'runtime': 334}, '_timestamp': 1680628699.1189623, 'test/recall': 0.8372093023255814, 'test/epoch_loss': 0.23338710864384968, 'train/batch_loss': 0.11391787976026536, 'train/epoch_loss': 0.2116023584907412, 'epoch': 9, '_runtime': 335.94198656082153, 'test/f1-score': 0.9, 'test/epoch_acc': 0.9111111111111112, 'test/precision': 0.972972972972973, 'train/epoch_acc': 0.9275184275184276}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0003}",cool-sweep-9
|
31,"{'test/f1-score': 0.9, 'test/epoch_acc': 0.9111111111111112, 'test/precision': 0.972972972972973, 'test/epoch_loss': 0.23338710864384968, 'train/epoch_acc': 0.9275184275184276, 'train/batch_loss': 0.11391787976026536, 'epoch': 9, '_wandb': {'runtime': 334}, 'train/epoch_loss': 0.2116023584907412, '_timestamp': 1680628699.1189623, 'test/recall': 0.8372093023255814, '_step': 1039, '_runtime': 335.94198656082153}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0003}",cool-sweep-9
|
||||||
32,"{'_runtime': 327.29265093803406, '_timestamp': 1680628351.790065, 'test/f1-score': 0.7959183673469388, 'train/epoch_loss': 0.6034659886828805, '_step': 529, '_wandb': {'runtime': 326}, 'test/recall': 0.8863636363636364, 'test/epoch_acc': 0.7777777777777778, 'test/precision': 0.7222222222222222, 'test/epoch_loss': 0.5824494547314114, 'train/epoch_acc': 0.7702702702702703, 'train/batch_loss': 0.5777762532234192, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0001}",lilac-sweep-8
|
32,"{'_timestamp': 1680628351.790065, 'test/recall': 0.8863636363636364, 'test/epoch_acc': 0.7777777777777778, 'train/epoch_acc': 0.7702702702702703, 'train/epoch_loss': 0.6034659886828805, 'epoch': 9, '_wandb': {'runtime': 326}, '_runtime': 327.29265093803406, 'test/epoch_loss': 0.5824494547314114, 'train/batch_loss': 0.5777762532234192, '_step': 529, 'test/f1-score': 0.7959183673469388, 'test/precision': 0.7222222222222222}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0001}",lilac-sweep-8
|
||||||
33,"{'_wandb': {'runtime': 335}, '_runtime': 337.11313247680664, 'test/recall': 0.8048780487804879, 'test/f1-score': 0.717391304347826, 'test/epoch_acc': 0.7111111111111111, 'test/epoch_loss': 0.6369305915302701, '_step': 149, 'epoch': 9, 'train/epoch_loss': 0.618001790392311, 'train/epoch_acc': 0.7199017199017199, 'train/batch_loss': 0.5935282111167908, '_timestamp': 1680628016.5942774, 'test/precision': 0.6470588235294118}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.001}",warm-sweep-7
|
33,"{'epoch': 9, '_runtime': 337.11313247680664, 'test/f1-score': 0.717391304347826, 'test/epoch_acc': 0.7111111111111111, 'test/epoch_loss': 0.6369305915302701, 'train/batch_loss': 0.5935282111167908, '_step': 149, '_timestamp': 1680628016.5942774, 'test/recall': 0.8048780487804879, 'test/precision': 0.6470588235294118, 'train/epoch_acc': 0.7199017199017199, 'train/epoch_loss': 0.618001790392311, '_wandb': {'runtime': 335}}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.001}",warm-sweep-7
|
||||||
34,"{'train/epoch_acc': 0.6498771498771498, 'train/epoch_loss': 0.6663250732773353, '_wandb': {'runtime': 354}, '_runtime': 355.7423675060272, 'test/recall': 0.8, 'test/f1-score': 0.6857142857142857, 'test/precision': 0.6, 'test/epoch_loss': 0.6619265423880683, '_step': 2059, 'epoch': 9, '_timestamp': 1680627667.6215644, 'test/epoch_acc': 0.6333333333333333, 'train/batch_loss': 0.6662057638168335}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.0001}",giddy-sweep-6
|
34,"{'_step': 2059, 'epoch': 9, '_wandb': {'runtime': 354}, '_runtime': 355.7423675060272, '_timestamp': 1680627667.6215644, 'test/epoch_acc': 0.6333333333333333, 'test/epoch_loss': 0.6619265423880683, 'train/epoch_acc': 0.6498771498771498, 'test/recall': 0.8, 'test/f1-score': 0.6857142857142857, 'test/precision': 0.6, 'train/batch_loss': 0.6662057638168335, 'train/epoch_loss': 0.6663250732773353}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.0001}",giddy-sweep-6
|
||||||
35,"{'test/recall': 0.8163265306122449, 'test/f1-score': 0.7766990291262137, 'test/epoch_acc': 0.7444444444444445, 'test/epoch_loss': 0.6307997491624621, 'train/epoch_acc': 0.7125307125307125, 'epoch': 9, '_runtime': 344.59358406066895, '_timestamp': 1680627305.434523, 'train/batch_loss': 0.6531811356544495, 'train/epoch_loss': 0.6398702088093582, '_step': 149, '_wandb': {'runtime': 343}, 'test/precision': 0.7407407407407407}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.0001}",stellar-sweep-5
|
35,"{'test/recall': 0.8163265306122449, 'test/f1-score': 0.7766990291262137, 'test/precision': 0.7407407407407407, 'test/epoch_loss': 0.6307997491624621, 'train/epoch_acc': 0.7125307125307125, 'train/batch_loss': 0.6531811356544495, '_wandb': {'runtime': 343}, '_runtime': 344.59358406066895, '_timestamp': 1680627305.434523, 'test/epoch_acc': 0.7444444444444445, 'train/epoch_loss': 0.6398702088093582, '_step': 149, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.0001}",stellar-sweep-5
|
||||||
36,"{'_runtime': 335.76391553878784, '_timestamp': 1680626951.0603056, 'test/recall': 0.8461538461538461, 'test/f1-score': 0.9041095890410958, 'test/precision': 0.9705882352941176, 'test/epoch_loss': 0.1906787835785912, 'epoch': 9, '_wandb': {'runtime': 334}, 'train/epoch_loss': 0.02095988139033052, 'train/epoch_acc': 0.9975429975429976, 'train/batch_loss': 0.0006497434806078672, '_step': 1039, 'test/epoch_acc': 0.9222222222222224}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",olive-sweep-4
|
36,"{'test/precision': 0.9705882352941176, 'test/epoch_loss': 0.1906787835785912, 'train/epoch_acc': 0.9975429975429976, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 334}, 'test/f1-score': 0.9041095890410958, 'train/batch_loss': 0.0006497434806078672, 'train/epoch_loss': 0.02095988139033052, '_runtime': 335.76391553878784, '_timestamp': 1680626951.0603056, 'test/recall': 0.8461538461538461, 'test/epoch_acc': 0.9222222222222224}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",olive-sweep-4
|
||||||
37,"{'_wandb': {'runtime': 332}, '_timestamp': 1680626608.419389, 'test/f1-score': 0.8705882352941177, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.8222222222222222, 'train/epoch_acc': 0.984029484029484, 'train/batch_loss': 0.12675245106220245, '_step': 149, 'epoch': 9, '_runtime': 333.64992809295654, 'test/recall': 0.925, 'test/epoch_loss': 0.27919367684258356, 'train/epoch_loss': 0.11751884335528429}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.003}",dazzling-sweep-3
|
37,"{'epoch': 9, '_runtime': 333.64992809295654, '_timestamp': 1680626608.419389, 'train/epoch_loss': 0.11751884335528429, 'train/epoch_acc': 0.984029484029484, '_step': 149, '_wandb': {'runtime': 332}, 'test/recall': 0.925, 'test/f1-score': 0.8705882352941177, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.8222222222222222, 'test/epoch_loss': 0.27919367684258356, 'train/batch_loss': 0.12675245106220245}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.003}",dazzling-sweep-3
|
||||||
38,"{'_runtime': 337.19885444641113, '_timestamp': 1680626264.5954974, 'test/f1-score': 0.5977011494252874, 'test/epoch_acc': 0.6111111111111112, 'test/precision': 0.5306122448979592, 'train/epoch_acc': 0.6547911547911548, 'epoch': 9, '_wandb': {'runtime': 336}, 'train/epoch_loss': 0.6389284106085868, 'test/epoch_loss': 0.6708752089076572, 'train/batch_loss': 0.5270536541938782, '_step': 1039, 'test/recall': 0.6842105263157895}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.01}",kind-sweep-2
|
38,"{'test/precision': 0.5306122448979592, '_wandb': {'runtime': 336}, '_timestamp': 1680626264.5954974, 'test/recall': 0.6842105263157895, 'test/epoch_acc': 0.6111111111111112, 'test/epoch_loss': 0.6708752089076572, 'train/epoch_acc': 0.6547911547911548, 'train/batch_loss': 0.5270536541938782, 'train/epoch_loss': 0.6389284106085868, '_step': 1039, 'epoch': 9, '_runtime': 337.19885444641113, 'test/f1-score': 0.5977011494252874}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.01}",kind-sweep-2
|
||||||
39,"{'epoch': 9, '_wandb': {'runtime': 337}, '_runtime': 337.9836483001709, 'test/recall': 0.8636363636363636, 'test/f1-score': 0.853932584269663, '_step': 529, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.8444444444444444, 'test/epoch_loss': 0.38614972366227046, 'train/epoch_acc': 0.8746928746928747, 'train/batch_loss': 0.3848239779472351, 'train/epoch_loss': 0.3516608065117782, '_timestamp': 1680625919.9645753}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.003}",morning-sweep-1
|
39,"{'train/epoch_loss': 0.3516608065117782, 'epoch': 9, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.8444444444444444, 'train/epoch_acc': 0.8746928746928747, 'train/batch_loss': 0.3848239779472351, 'test/f1-score': 0.853932584269663, 'test/epoch_loss': 0.38614972366227046, '_step': 529, '_wandb': {'runtime': 337}, '_runtime': 337.9836483001709, '_timestamp': 1680625919.9645753, 'test/recall': 0.8636363636363636}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.003}",morning-sweep-1
|
||||||
40,"{'test/recall': 0.8653846153846154, 'test/f1-score': 0.9, 'train/batch_loss': 0.05631007254123688, '_step': 2059, '_timestamp': 1680624250.2654595, '_runtime': 347.9354045391083, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9375, 'test/epoch_loss': 0.25786760796585845, 'train/epoch_acc': 0.9975429975429976, 'train/epoch_loss': 0.02368298517580857, 'epoch': 9, '_wandb': {'runtime': 346}}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.1}",valiant-sweep-23
|
40,"{'train/epoch_loss': 0.02368298517580857, 'epoch': 9, 'test/recall': 0.8653846153846154, 'test/f1-score': 0.9, 'test/precision': 0.9375, 'test/epoch_acc': 0.888888888888889, 'test/epoch_loss': 0.25786760796585845, 'train/epoch_acc': 0.9975429975429976, 'train/batch_loss': 0.05631007254123688, '_step': 2059, '_wandb': {'runtime': 346}, '_runtime': 347.9354045391083, '_timestamp': 1680624250.2654595}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.1}",valiant-sweep-23
|
||||||
41,"{'_runtime': 329.4802031517029, '_timestamp': 1680623895.362503, 'test/recall': 0.8936170212765957, 'test/f1-score': 0.8571428571428571, 'test/epoch_loss': 0.490613665845659, 'train/epoch_acc': 0.8243243243243243, 'epoch': 9, '_wandb': {'runtime': 327}, 'test/epoch_acc': 0.8444444444444444, 'test/precision': 0.8235294117647058, 'train/batch_loss': 0.5639374256134033, 'train/epoch_loss': 0.48581602795996887, '_step': 1039}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0003}",earnest-sweep-22
|
41,"{'train/batch_loss': 0.5639374256134033, '_timestamp': 1680623895.362503, 'test/recall': 0.8936170212765957, 'test/f1-score': 0.8571428571428571, 'test/epoch_acc': 0.8444444444444444, 'test/precision': 0.8235294117647058, 'test/epoch_loss': 0.490613665845659, 'train/epoch_acc': 0.8243243243243243, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 327}, '_runtime': 329.4802031517029, 'train/epoch_loss': 0.48581602795996887}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0003}",earnest-sweep-22
|
||||||
42,"{'_step': 149, 'epoch': 9, '_timestamp': 1680623556.4586525, 'test/recall': 0.9148936170212766, 'test/epoch_loss': 0.2318242397573259, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.06110217794775963, 'train/epoch_loss': 0.05107141801451289, '_wandb': {'runtime': 326}, '_runtime': 328.0050995349884, 'test/f1-score': 0.9052631578947368, 'test/epoch_acc': 0.9, 'test/precision': 0.8958333333333334}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",genial-sweep-21
|
42,"{'_timestamp': 1680623556.4586525, 'test/recall': 0.9148936170212766, 'test/f1-score': 0.9052631578947368, 'test/epoch_acc': 0.9, 'test/precision': 0.8958333333333334, 'test/epoch_loss': 0.2318242397573259, 'train/epoch_acc': 0.995085995085995, 'epoch': 9, '_wandb': {'runtime': 326}, '_runtime': 328.0050995349884, 'train/batch_loss': 0.06110217794775963, 'train/epoch_loss': 0.05107141801451289, '_step': 149}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",genial-sweep-21
|
||||||
43,"{'_wandb': {'runtime': 325}, '_runtime': 327.10622239112854, '_timestamp': 1680623221.0825984, 'test/recall': 0.8723404255319149, 'train/epoch_acc': 0.7911547911547911, '_step': 149, 'epoch': 9, 'test/f1-score': 0.780952380952381, 'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.7068965517241379, 'test/epoch_loss': 0.5943129923608568, 'train/batch_loss': 0.6166229844093323, 'train/epoch_loss': 0.5714027147914034}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",lemon-sweep-20
|
43,"{'_runtime': 327.10622239112854, '_timestamp': 1680623221.0825984, 'test/recall': 0.8723404255319149, 'test/epoch_acc': 0.7444444444444445, 'test/epoch_loss': 0.5943129923608568, 'train/epoch_acc': 0.7911547911547911, '_step': 149, '_wandb': {'runtime': 325}, 'train/epoch_loss': 0.5714027147914034, 'test/precision': 0.7068965517241379, 'train/batch_loss': 0.6166229844093323, 'epoch': 9, 'test/f1-score': 0.780952380952381}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",lemon-sweep-20
|
||||||
44,"{'train/epoch_acc': 0.6277641277641277, 'train/epoch_loss': 0.6722187732302879, 'epoch': 9, '_wandb': {'runtime': 330}, '_runtime': 331.60892701148987, 'test/recall': 0.7021276595744681, 'test/f1-score': 0.6470588235294118, 'train/batch_loss': 0.7205827236175537, '_step': 1039, '_timestamp': 1680622885.059607, 'test/epoch_acc': 0.6, 'test/precision': 0.6, 'test/epoch_loss': 0.6746161646313138}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",ancient-sweep-19
|
44,"{'_runtime': 331.60892701148987, 'test/recall': 0.7021276595744681, 'test/epoch_acc': 0.6, 'test/precision': 0.6, 'test/epoch_loss': 0.6746161646313138, 'train/batch_loss': 0.7205827236175537, '_step': 1039, '_wandb': {'runtime': 330}, '_timestamp': 1680622885.059607, 'test/f1-score': 0.6470588235294118, 'train/epoch_acc': 0.6277641277641277, 'train/epoch_loss': 0.6722187732302879, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",ancient-sweep-19
|
||||||
45,"{'test/epoch_loss': 0.24883262103216516, 'train/epoch_acc': 0.9877149877149876, 'train/batch_loss': 0.015468262135982512, '_wandb': {'runtime': 347}, '_runtime': 348.9979507923126, '_timestamp': 1680622545.2735748, 'test/recall': 0.8695652173913043, 'test/f1-score': 0.898876404494382, 'test/epoch_acc': 0.9, 'test/precision': 0.9302325581395348, 'train/epoch_loss': 0.0466749508011656, '_step': 2059, 'epoch': 9}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.01}",smart-sweep-18
|
45,"{'_wandb': {'runtime': 347}, '_runtime': 348.9979507923126, '_timestamp': 1680622545.2735748, 'test/f1-score': 0.898876404494382, 'test/epoch_acc': 0.9, 'test/epoch_loss': 0.24883262103216516, '_step': 2059, 'epoch': 9, 'train/epoch_acc': 0.9877149877149876, 'train/epoch_loss': 0.0466749508011656, 'train/batch_loss': 0.015468262135982512, 'test/recall': 0.8695652173913043, 'test/precision': 0.9302325581395348}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.01}",smart-sweep-18
|
||||||
46,"{'epoch': 9, '_runtime': 329.3028633594513, '_timestamp': 1680622188.8210304, 'test/epoch_loss': 0.2015038196825319, 'train/epoch_loss': 0.07856258183731457, '_step': 1039, 'test/recall': 0.8536585365853658, 'test/f1-score': 0.8974358974358975, 'test/epoch_acc': 0.9111111111111112, 'test/precision': 0.945945945945946, 'train/epoch_acc': 0.9815724815724816, 'train/batch_loss': 0.007225348148494959, '_wandb': {'runtime': 328}}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.003}",sleek-sweep-17
|
46,"{'test/precision': 0.945945945945946, 'epoch': 9, '_wandb': {'runtime': 328}, '_runtime': 329.3028633594513, '_timestamp': 1680622188.8210304, 'test/recall': 0.8536585365853658, 'test/f1-score': 0.8974358974358975, '_step': 1039, 'test/epoch_acc': 0.9111111111111112, 'test/epoch_loss': 0.2015038196825319, 'train/epoch_acc': 0.9815724815724816, 'train/batch_loss': 0.007225348148494959, 'train/epoch_loss': 0.07856258183731457}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.003}",sleek-sweep-17
|
||||||
47,"{'test/epoch_acc': 0.8333333333333334, 'train/epoch_acc': 0.828009828009828, 'train/epoch_loss': 0.5808350268101516, 'test/recall': 0.8301886792452831, 'epoch': 9, '_wandb': {'runtime': 321}, '_runtime': 323.3842430114746, '_timestamp': 1680621849.979658, 'test/f1-score': 0.8543689320388349, 'test/precision': 0.88, 'test/epoch_loss': 0.5843977000978258, '_step': 279, 'train/batch_loss': 0.6047794222831726}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.0001}",winter-sweep-16
|
47,"{'_step': 279, 'epoch': 9, '_wandb': {'runtime': 321}, '_timestamp': 1680621849.979658, 'train/epoch_acc': 0.828009828009828, 'train/batch_loss': 0.6047794222831726, 'train/epoch_loss': 0.5808350268101516, '_runtime': 323.3842430114746, 'test/recall': 0.8301886792452831, 'test/f1-score': 0.8543689320388349, 'test/epoch_acc': 0.8333333333333334, 'test/precision': 0.88, 'test/epoch_loss': 0.5843977000978258}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.0001}",winter-sweep-16
|
||||||
48,"{'epoch': 9, '_wandb': {'runtime': 346}, '_runtime': 347.8050694465637, 'test/recall': 0.85, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.85, '_step': 2059, 'test/f1-score': 0.85, 'test/epoch_loss': 0.5281610590923164, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.001602485659532249, 'train/epoch_loss': 0.029015880939893934, '_timestamp': 1680621511.323635}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.1}",rare-sweep-15
|
48,"{'test/recall': 0.85, 'train/batch_loss': 0.001602485659532249, 'epoch': 9, '_wandb': {'runtime': 346}, '_timestamp': 1680621511.323635, 'test/f1-score': 0.85, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.85, 'test/epoch_loss': 0.5281610590923164, 'train/epoch_acc': 0.995085995085995, '_step': 2059, '_runtime': 347.8050694465637, 'train/epoch_loss': 0.029015880939893934}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.1}",rare-sweep-15
|
||||||
49,"{'_wandb': {'runtime': 346}, '_runtime': 347.7671456336975, '_timestamp': 1680621147.5604067, 'test/f1-score': 0.9135802469135802, 'test/epoch_acc': 0.9222222222222224, 'train/epoch_acc': 0.9864864864864864, '_step': 2059, 'test/recall': 0.8809523809523809, 'test/precision': 0.9487179487179488, 'test/epoch_loss': 0.22225395898438163, 'train/batch_loss': 0.010366588830947876, 'train/epoch_loss': 0.04606454834343147, 'epoch': 9}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.001}",stoic-sweep-14
|
49,"{'_step': 2059, 'epoch': 9, '_wandb': {'runtime': 346}, '_runtime': 347.7671456336975, 'test/epoch_acc': 0.9222222222222224, 'test/precision': 0.9487179487179488, 'train/epoch_loss': 0.04606454834343147, '_timestamp': 1680621147.5604067, 'test/recall': 0.8809523809523809, 'test/f1-score': 0.9135802469135802, 'test/epoch_loss': 0.22225395898438163, 'train/epoch_acc': 0.9864864864864864, 'train/batch_loss': 0.010366588830947876}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.001}",stoic-sweep-14
|
||||||
50,"{'_timestamp': 1680620790.920825, 'test/f1-score': 0.6585365853658537, 'train/epoch_acc': 0.6523341523341524, 'train/batch_loss': 0.6023905277252197, 'train/epoch_loss': 0.6673213337211703, '_step': 2059, '_wandb': {'runtime': 351}, '_runtime': 352.6435329914093, 'test/precision': 0.6428571428571429, 'test/epoch_loss': 0.661226307021247, 'epoch': 9, 'test/recall': 0.675, 'test/epoch_acc': 0.6888888888888889}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.0001}",glorious-sweep-13
|
50,"{'train/epoch_acc': 0.6523341523341524, 'train/batch_loss': 0.6023905277252197, '_wandb': {'runtime': 351}, '_timestamp': 1680620790.920825, 'test/recall': 0.675, 'test/f1-score': 0.6585365853658537, 'test/precision': 0.6428571428571429, 'test/epoch_loss': 0.661226307021247, 'train/epoch_loss': 0.6673213337211703, '_step': 2059, 'epoch': 9, '_runtime': 352.6435329914093, 'test/epoch_acc': 0.6888888888888889}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.0001}",glorious-sweep-13
|
||||||
51,"{'_step': 149, '_wandb': {'runtime': 329}, 'test/recall': 0.9574468085106383, 'test/f1-score': 0.9782608695652174, 'test/epoch_acc': 0.977777777777778, 'test/precision': 1, 'train/epoch_acc': 1, 'epoch': 9, '_runtime': 330.7649688720703, '_timestamp': 1680620431.024078, 'test/epoch_loss': 0.1352142873737547, 'train/batch_loss': 0.004083937965333462, 'train/epoch_loss': 0.0071195896911716286}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",chocolate-sweep-12
|
51,"{'epoch': 9, '_wandb': {'runtime': 329}, 'test/recall': 0.9574468085106383, 'test/f1-score': 0.9782608695652174, 'test/precision': 1, 'train/batch_loss': 0.004083937965333462, 'train/epoch_loss': 0.0071195896911716286, '_step': 149, '_runtime': 330.7649688720703, '_timestamp': 1680620431.024078, 'test/epoch_acc': 0.977777777777778, 'test/epoch_loss': 0.1352142873737547, 'train/epoch_acc': 1}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",chocolate-sweep-12
|
||||||
52,"{'test/precision': 0.8085106382978723, 'train/epoch_loss': 0.5577488642652731, '_step': 149, 'epoch': 9, '_wandb': {'runtime': 328}, '_timestamp': 1680620092.0697718, 'test/f1-score': 0.8636363636363636, 'test/epoch_acc': 0.8666666666666667, '_runtime': 329.12984681129456, 'test/recall': 0.926829268292683, 'test/epoch_loss': 0.5375637359089321, 'train/epoch_acc': 0.800982800982801, 'train/batch_loss': 0.5299303531646729}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.0003}",glowing-sweep-11
|
52,"{'train/epoch_loss': 0.5577488642652731, '_step': 149, '_wandb': {'runtime': 328}, 'test/recall': 0.926829268292683, 'test/f1-score': 0.8636363636363636, 'test/precision': 0.8085106382978723, 'train/epoch_acc': 0.800982800982801, 'train/batch_loss': 0.5299303531646729, 'epoch': 9, '_runtime': 329.12984681129456, '_timestamp': 1680620092.0697718, 'test/epoch_acc': 0.8666666666666667, 'test/epoch_loss': 0.5375637359089321}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.0003}",glowing-sweep-11
|
||||||
53,"{'_runtime': 324.3058567047119, 'test/recall': 0.7659574468085106, 'test/epoch_acc': 0.7555555555555555, 'test/precision': 0.7659574468085106, 'train/epoch_acc': 0.8611793611793611, 'train/epoch_loss': 0.46212616409072127, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 322}, '_timestamp': 1680619755.0191748, 'test/f1-score': 0.7659574468085105, 'test/epoch_loss': 0.5337554746203952, 'train/batch_loss': 0.5281365513801575}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",different-sweep-10
|
53,"{'train/epoch_acc': 0.8611793611793611, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 322}, '_timestamp': 1680619755.0191748, 'test/f1-score': 0.7659574468085105, 'train/batch_loss': 0.5281365513801575, 'train/epoch_loss': 0.46212616409072127, '_runtime': 324.3058567047119, 'test/recall': 0.7659574468085106, 'test/epoch_acc': 0.7555555555555555, 'test/precision': 0.7659574468085106, 'test/epoch_loss': 0.5337554746203952}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",different-sweep-10
|
||||||
54,"{'_runtime': 327.0705659389496, '_timestamp': 1680619423.656795, 'test/f1-score': 0.8602150537634408, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.7843137254901961, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 325}, 'test/epoch_loss': 0.5470490535100301, 'train/epoch_acc': 0.8058968058968059, 'train/epoch_loss': 0.5580001385557564, 'test/recall': 0.9523809523809524, 'train/batch_loss': 0.6183260083198547}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.003}",lilac-sweep-9
|
54,"{'test/epoch_loss': 0.5470490535100301, 'train/batch_loss': 0.6183260083198547, '_step': 279, 'epoch': 9, '_runtime': 327.0705659389496, '_timestamp': 1680619423.656795, 'test/recall': 0.9523809523809524, 'test/precision': 0.7843137254901961, '_wandb': {'runtime': 325}, 'test/f1-score': 0.8602150537634408, 'test/epoch_acc': 0.8555555555555556, 'train/epoch_acc': 0.8058968058968059, 'train/epoch_loss': 0.5580001385557564}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.003}",lilac-sweep-9
|
||||||
55,"{'train/epoch_loss': 0.46969629490990605, '_wandb': {'runtime': 327}, 'test/recall': 0.7551020408163265, 'test/epoch_acc': 0.788888888888889, 'test/precision': 0.8409090909090909, 'test/f1-score': 0.7956989247311828, 'test/epoch_loss': 0.46168507006433274, 'train/epoch_acc': 0.773955773955774, 'train/batch_loss': 0.6300776600837708, '_step': 529, 'epoch': 9, '_runtime': 328.68579959869385, '_timestamp': 1680619089.5332966}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",crimson-sweep-8
|
55,"{'test/f1-score': 0.7956989247311828, 'test/precision': 0.8409090909090909, 'train/batch_loss': 0.6300776600837708, '_step': 529, 'epoch': 9, '_runtime': 328.68579959869385, '_timestamp': 1680619089.5332966, 'test/recall': 0.7551020408163265, 'train/epoch_loss': 0.46969629490990605, '_wandb': {'runtime': 327}, 'test/epoch_acc': 0.788888888888889, 'test/epoch_loss': 0.46168507006433274, 'train/epoch_acc': 0.773955773955774}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",crimson-sweep-8
|
||||||
56,"{'_step': 2059, '_runtime': 350.2308712005615, '_timestamp': 1680618753.2361271, 'test/epoch_loss': 0.44089303129391433, 'train/epoch_acc': 0.9938574938574938, 'train/batch_loss': 0.011611333116889, 'epoch': 9, '_wandb': {'runtime': 349}, 'test/recall': 0.8181818181818182, 'test/f1-score': 0.8737864077669902, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.9375, 'train/epoch_loss': 0.02176519967463292}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.003}",still-sweep-7
|
56,"{'test/recall': 0.8181818181818182, 'test/epoch_loss': 0.44089303129391433, 'train/epoch_acc': 0.9938574938574938, 'train/epoch_loss': 0.02176519967463292, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.9375, '_step': 2059, 'epoch': 9, '_wandb': {'runtime': 349}, '_runtime': 350.2308712005615, '_timestamp': 1680618753.2361271, 'test/f1-score': 0.8737864077669902, 'train/batch_loss': 0.011611333116889}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.003}",still-sweep-7
|
||||||
57,"{'test/f1-score': 0.8607594936708861, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.85, 'train/epoch_acc': 0.9938574938574938, 'train/epoch_loss': 0.02099113287724536, '_wandb': {'runtime': 333}, 'test/recall': 0.8717948717948718, '_runtime': 334.69481587409973, '_timestamp': 1680618396.0194488, 'test/epoch_loss': 0.24035142682841976, 'train/batch_loss': 0.030084805563092232, '_step': 1039, 'epoch': 9}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.01}",charmed-sweep-6
|
57,"{'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.85, 'test/epoch_loss': 0.24035142682841976, 'train/epoch_acc': 0.9938574938574938, 'epoch': 9, '_wandb': {'runtime': 333}, 'test/recall': 0.8717948717948718, 'test/f1-score': 0.8607594936708861, 'train/epoch_loss': 0.02099113287724536, '_step': 1039, '_runtime': 334.69481587409973, '_timestamp': 1680618396.0194488, 'train/batch_loss': 0.030084805563092232}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.01}",charmed-sweep-6
|
||||||
58,"{'epoch': 9, '_timestamp': 1680618051.044084, 'test/recall': 0.8780487804878049, 'test/f1-score': 0.8674698795180722, 'test/precision': 0.8571428571428571, 'test/epoch_loss': 0.5385394818252988, 'train/epoch_acc': 0.9963144963144964, 'train/batch_loss': 0.001848929445259273, '_step': 1039, '_wandb': {'runtime': 335}, '_runtime': 336.1621870994568, 'test/epoch_acc': 0.8777777777777778, 'train/epoch_loss': 0.010693324584853135}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0003}",restful-sweep-5
|
58,"{'epoch': 9, '_wandb': {'runtime': 335}, '_timestamp': 1680618051.044084, 'train/epoch_acc': 0.9963144963144964, 'train/epoch_loss': 0.010693324584853135, '_step': 1039, 'test/recall': 0.8780487804878049, 'test/f1-score': 0.8674698795180722, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.8571428571428571, 'test/epoch_loss': 0.5385394818252988, 'train/batch_loss': 0.001848929445259273, '_runtime': 336.1621870994568}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0003}",restful-sweep-5
|
||||||
59,"{'_step': 149, 'epoch': 9, 'test/recall': 0.8409090909090909, 'test/epoch_acc': 0.8444444444444444, 'test/epoch_loss': 0.6238909363746643, 'train/epoch_loss': 0.004462716538065481, '_wandb': {'runtime': 333}, '_runtime': 334.4848310947418, '_timestamp': 1680617708.075962, 'test/f1-score': 0.8409090909090909, 'test/precision': 0.8409090909090909, 'train/epoch_acc': 1, 'train/batch_loss': 0.004928763955831528}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",proud-sweep-4
|
59,"{'train/epoch_acc': 1, 'train/batch_loss': 0.004928763955831528, 'train/epoch_loss': 0.004462716538065481, '_step': 149, '_runtime': 334.4848310947418, 'test/f1-score': 0.8409090909090909, 'test/epoch_acc': 0.8444444444444444, 'test/precision': 0.8409090909090909, 'epoch': 9, '_wandb': {'runtime': 333}, '_timestamp': 1680617708.075962, 'test/recall': 0.8409090909090909, 'test/epoch_loss': 0.6238909363746643}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",proud-sweep-4
|
||||||
60,"{'train/epoch_acc': 0.5626535626535626, 'train/batch_loss': 0.6750851273536682, '_step': 149, '_wandb': {'runtime': 337}, '_timestamp': 1680617365.2791553, 'test/recall': 0.75, 'test/epoch_acc': 0.34444444444444444, 'test/epoch_loss': 0.7233364171451993, 'train/epoch_loss': 0.6796711432845938, 'epoch': 9, '_runtime': 338.4922821521759, 'test/f1-score': 0.4778761061946903, 'test/precision': 0.35064935064935066}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.0001}",visionary-sweep-3
|
60,"{'epoch': 9, '_runtime': 338.4922821521759, '_timestamp': 1680617365.2791553, 'test/recall': 0.75, 'test/f1-score': 0.4778761061946903, 'test/precision': 0.35064935064935066, 'test/epoch_loss': 0.7233364171451993, 'train/epoch_acc': 0.5626535626535626, 'train/batch_loss': 0.6750851273536682, 'train/epoch_loss': 0.6796711432845938, '_step': 149, '_wandb': {'runtime': 337}, 'test/epoch_acc': 0.34444444444444444}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.0001}",visionary-sweep-3
|
||||||
61,"{'_wandb': {'runtime': 132}, 'test/recall': 1, 'test/f1-score': 0.59375, 'test/epoch_acc': 0.4222222222222222, 'test/precision': 0.4222222222222222, 'train/batch_loss': 1.2695436477661133, '_step': 110, 'epoch': 3, '_runtime': 129.48883533477783, '_timestamp': 1680617007.4126654, 'test/epoch_loss': 109.22879723442924, 'train/epoch_acc': 0.5147420147420148, 'train/epoch_loss': 3.225923076601521}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.1}",splendid-sweep-2
|
61,"{'test/recall': 1, 'test/f1-score': 0.59375, 'test/epoch_loss': 109.22879723442924, 'train/epoch_acc': 0.5147420147420148, '_step': 110, 'epoch': 3, '_runtime': 129.48883533477783, '_timestamp': 1680617007.4126654, 'train/batch_loss': 1.2695436477661133, 'train/epoch_loss': 3.225923076601521, '_wandb': {'runtime': 132}, 'test/epoch_acc': 0.4222222222222222, 'test/precision': 0.4222222222222222}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.1}",splendid-sweep-2
|
||||||
62,"{'_runtime': 373.84231185913086, 'test/recall': 0.8636363636363636, 'train/batch_loss': 0.563504695892334, 'test/epoch_loss': 0.6018742865986294, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 372}, '_timestamp': 1680616870.0621138, 'test/f1-score': 0.8172043010752688, 'test/epoch_acc': 0.8111111111111111, 'test/precision': 0.7755102040816326, 'train/epoch_acc': 0.7727272727272727, 'train/epoch_loss': 0.5949591096554693}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0001}",snowy-sweep-1
|
62,"{'train/epoch_loss': 0.5949591096554693, '_step': 1039, 'epoch': 9, 'test/recall': 0.8636363636363636, 'test/f1-score': 0.8172043010752688, 'test/precision': 0.7755102040816326, 'test/epoch_loss': 0.6018742865986294, '_wandb': {'runtime': 372}, '_runtime': 373.84231185913086, '_timestamp': 1680616870.0621138, 'test/epoch_acc': 0.8111111111111111, 'train/epoch_acc': 0.7727272727272727, 'train/batch_loss': 0.563504695892334}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0001}",snowy-sweep-1
|
||||||
63,"{'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.625, 'train/epoch_acc': 0.5552825552825553, 'train/batch_loss': 0.7118003964424133, 'epoch': 9, '_timestamp': 1678798635.5359335, 'test/f1-score': 0.6024096385542168, 'test/recall': 0.5813953488372093, 'test/epoch_loss': 0.6787986318270366, 'train/epoch_loss': 0.684732110699506, '_step': 529, '_wandb': {'runtime': 327}, '_runtime': 333.6077947616577}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.0001}",comic-sweep-38
|
63,"{'_timestamp': 1678798635.5359335, 'test/recall': 0.5813953488372093, 'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.625, 'train/epoch_loss': 0.684732110699506, '_step': 529, '_runtime': 333.6077947616577, 'test/f1-score': 0.6024096385542168, 'test/epoch_loss': 0.6787986318270366, 'train/epoch_acc': 0.5552825552825553, 'train/batch_loss': 0.7118003964424133, 'epoch': 9, '_wandb': {'runtime': 327}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.0001}",comic-sweep-38
|
||||||
64,"{'_step': 149, 'epoch': 9, '_timestamp': 1678798288.876002, 'test/recall': 1, 'test/epoch_loss': 0.5120628664890925, 'train/epoch_acc': 1, 'train/epoch_loss': 0.001254009526264133, '_wandb': {'runtime': 337}, '_runtime': 342.7867271900177, 'test/f1-score': 0.888888888888889, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.8, 'train/batch_loss': 0.0015535189304500818}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",magic-sweep-37
|
64,"{'test/epoch_loss': 0.5120628664890925, 'train/epoch_acc': 1, '_wandb': {'runtime': 337}, '_runtime': 342.7867271900177, '_timestamp': 1678798288.876002, 'test/recall': 1, 'test/f1-score': 0.888888888888889, 'test/precision': 0.8, 'train/epoch_loss': 0.001254009526264133, '_step': 149, 'epoch': 9, 'test/epoch_acc': 0.888888888888889, 'train/batch_loss': 0.0015535189304500818}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",magic-sweep-37
|
||||||
65,"{'test/recall': 0.6341463414634146, 'test/epoch_acc': 0.6444444444444445, 'test/precision': 0.6046511627906976, 'train/epoch_acc': 0.6572481572481572, 'train/epoch_loss': 0.659313001562395, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 332}, 'test/epoch_loss': 0.6593369828330146, 'train/batch_loss': 0.6705241203308105, '_runtime': 338.4290623664856, '_timestamp': 1678797929.8979273, 'test/f1-score': 0.6190476190476191}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 32, 'learning_rate': 0.0003}",azure-sweep-36
|
65,"{'test/f1-score': 0.6190476190476191, 'test/epoch_loss': 0.6593369828330146, 'train/batch_loss': 0.6705241203308105, 'train/epoch_loss': 0.659313001562395, 'epoch': 9, '_runtime': 338.4290623664856, '_timestamp': 1678797929.8979273, 'test/recall': 0.6341463414634146, 'test/epoch_acc': 0.6444444444444445, 'test/precision': 0.6046511627906976, 'train/epoch_acc': 0.6572481572481572, '_step': 279, '_wandb': {'runtime': 332}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 32, 'learning_rate': 0.0003}",azure-sweep-36
|
||||||
66,"{'_step': 1039, 'test/precision': 0.9591836734693876, 'test/epoch_loss': 0.5167779392666287, 'train/epoch_acc': 0.7911547911547911, 'epoch': 9, '_wandb': {'runtime': 343}, '_runtime': 349.1018385887146, '_timestamp': 1678797575.4461255, 'test/recall': 0.8703703703703703, 'test/f1-score': 0.912621359223301, 'test/epoch_acc': 0.9, 'train/batch_loss': 0.5475739240646362, 'train/epoch_loss': 0.542006236622316}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",easy-sweep-35
|
66,"{'test/epoch_acc': 0.9, 'test/epoch_loss': 0.5167779392666287, '_step': 1039, '_wandb': {'runtime': 343}, '_timestamp': 1678797575.4461255, 'test/recall': 0.8703703703703703, 'test/f1-score': 0.912621359223301, 'test/precision': 0.9591836734693876, 'train/epoch_acc': 0.7911547911547911, 'train/batch_loss': 0.5475739240646362, 'epoch': 9, '_runtime': 349.1018385887146, 'train/epoch_loss': 0.542006236622316}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",easy-sweep-35
|
||||||
67,"{'_wandb': {'runtime': 362}, '_timestamp': 1678797212.2311337, 'test/f1-score': 0.8611111111111112, 'test/precision': 0.8611111111111112, 'test/epoch_loss': 0.27850865055532065, 'train/epoch_acc': 0.9987714987714988, 'train/batch_loss': 4.9947026127483696e-05, '_step': 2059, 'train/epoch_loss': 0.012833298822080874, '_runtime': 367.9372293949127, 'test/recall': 0.8611111111111112, 'test/epoch_acc': 0.888888888888889, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.003}",usual-sweep-34
|
67,"{'test/epoch_loss': 0.27850865055532065, 'train/batch_loss': 4.9947026127483696e-05, 'train/epoch_loss': 0.012833298822080874, '_timestamp': 1678797212.2311337, 'test/recall': 0.8611111111111112, '_wandb': {'runtime': 362}, '_runtime': 367.9372293949127, 'test/f1-score': 0.8611111111111112, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.8611111111111112, 'train/epoch_acc': 0.9987714987714988, '_step': 2059, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.003}",usual-sweep-34
|
||||||
68,"{'test/epoch_loss': 0.6554473309053315, 'epoch': 9, '_wandb': {'runtime': 330}, '_runtime': 335.99687933921814, '_timestamp': 1678796827.8409674, 'test/recall': 0.9791666666666666, 'test/f1-score': 0.903846153846154, 'test/epoch_acc': 0.888888888888889, 'train/epoch_acc': 0.9742014742014742, 'train/batch_loss': 0.17918632924556732, 'train/epoch_loss': 0.07036763163974523, '_step': 529, 'test/precision': 0.8392857142857143}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.0003}",polar-sweep-33
|
68,"{'_step': 529, '_runtime': 335.99687933921814, 'test/f1-score': 0.903846153846154, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.8392857142857143, 'test/epoch_loss': 0.6554473309053315, 'epoch': 9, '_wandb': {'runtime': 330}, '_timestamp': 1678796827.8409674, 'test/recall': 0.9791666666666666, 'train/epoch_acc': 0.9742014742014742, 'train/batch_loss': 0.17918632924556732, 'train/epoch_loss': 0.07036763163974523}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.0003}",polar-sweep-33
|
||||||
69,"{'test/f1-score': 0.7356321839080459, 'test/epoch_acc': 0.7444444444444445, 'train/epoch_acc': 0.8660933660933661, 'train/epoch_loss': 0.47513497564072105, 'epoch': 9, '_runtime': 336.63737440109253, '_timestamp': 1678796468.9253614, 'test/recall': 0.8648648648648649, 'test/precision': 0.64, 'test/epoch_loss': 0.5271965821584066, 'train/batch_loss': 0.4695126414299011, '_step': 149, '_wandb': {'runtime': 330}}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",still-sweep-32
|
69,"{'epoch': 9, '_runtime': 336.63737440109253, 'test/f1-score': 0.7356321839080459, 'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.64, 'test/epoch_loss': 0.5271965821584066, 'train/epoch_acc': 0.8660933660933661, 'train/epoch_loss': 0.47513497564072105, '_step': 149, '_wandb': {'runtime': 330}, '_timestamp': 1678796468.9253614, 'test/recall': 0.8648648648648649, 'train/batch_loss': 0.4695126414299011}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.001}",still-sweep-32
|
||||||
70,"{'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9428571428571428, 'test/epoch_loss': 0.2378266812198692, 'train/batch_loss': 0.711412787437439, '_step': 2059, '_wandb': {'runtime': 372}, '_runtime': 378.4032835960388, '_timestamp': 1678796117.3062005, 'test/recall': 0.8048780487804879, 'test/f1-score': 0.868421052631579, 'train/epoch_acc': 0.9705159705159704, 'train/epoch_loss': 0.09577267487700432, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.001}",misty-sweep-31
|
70,"{'train/batch_loss': 0.711412787437439, 'train/epoch_loss': 0.09577267487700432, '_step': 2059, 'epoch': 9, '_wandb': {'runtime': 372}, '_timestamp': 1678796117.3062005, 'test/f1-score': 0.868421052631579, 'test/epoch_acc': 0.888888888888889, '_runtime': 378.4032835960388, 'test/recall': 0.8048780487804879, 'test/precision': 0.9428571428571428, 'test/epoch_loss': 0.2378266812198692, 'train/epoch_acc': 0.9705159705159704}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.001}",misty-sweep-31
|
||||||
71,"{'_wandb': {'runtime': 333}, '_runtime': 336.8808288574219, '_timestamp': 1678795725.918603, 'test/f1-score': 0.8636363636363636, 'train/epoch_acc': 0.9926289926289926, 'train/epoch_loss': 0.05967479737370254, '_step': 529, 'epoch': 9, 'test/recall': 0.8260869565217391, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.9047619047619048, 'test/epoch_loss': 0.27924135790930854, 'train/batch_loss': 0.04936826974153519}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.001}",flowing-sweep-30
|
71,"{'_step': 529, 'epoch': 9, '_wandb': {'runtime': 333}, '_runtime': 336.8808288574219, '_timestamp': 1678795725.918603, 'test/recall': 0.8260869565217391, 'test/f1-score': 0.8636363636363636, 'test/epoch_acc': 0.8666666666666667, 'train/epoch_acc': 0.9926289926289926, 'test/precision': 0.9047619047619048, 'test/epoch_loss': 0.27924135790930854, 'train/batch_loss': 0.04936826974153519, 'train/epoch_loss': 0.05967479737370254}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.001}",flowing-sweep-30
|
||||||
72,"{'_runtime': 339.73244285583496, '_timestamp': 1678795319.518895, 'test/recall': 0.851063829787234, 'test/f1-score': 0.898876404494382, 'test/epoch_acc': 0.9, 'test/precision': 0.9523809523809524, '_step': 279, 'epoch': 9, 'train/epoch_acc': 0.8722358722358722, 'train/epoch_loss': 0.3784469199122024, 'train/batch_loss': 0.4592914581298828, '_wandb': {'runtime': 336}, 'test/epoch_loss': 0.37525106337335373}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.001}",deep-sweep-28
|
72,"{'_step': 279, 'epoch': 9, '_wandb': {'runtime': 336}, '_runtime': 339.73244285583496, 'test/f1-score': 0.898876404494382, 'test/epoch_acc': 0.9, 'test/precision': 0.9523809523809524, 'test/epoch_loss': 0.37525106337335373, 'train/epoch_loss': 0.3784469199122024, '_timestamp': 1678795319.518895, 'test/recall': 0.851063829787234, 'train/epoch_acc': 0.8722358722358722, 'train/batch_loss': 0.4592914581298828}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.001}",deep-sweep-28
|
||||||
73,"{'test/recall': 0.625, 'test/f1-score': 0.6849315068493151, 'train/epoch_acc': 0.7899262899262899, 'train/batch_loss': 0.6763702630996704, 'train/epoch_loss': 0.5319552311733255, '_wandb': {'runtime': 377}, '_runtime': 381.0768678188324, '_timestamp': 1678794965.2675128, 'test/precision': 0.7575757575757576, 'test/epoch_loss': 0.5484810524516636, '_step': 2059, 'epoch': 9, 'test/epoch_acc': 0.7444444444444445}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.0001}",glorious-sweep-27
|
73,"{'_timestamp': 1678794965.2675128, 'test/f1-score': 0.6849315068493151, 'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.7575757575757576, 'test/epoch_loss': 0.5484810524516636, 'epoch': 9, '_wandb': {'runtime': 377}, '_runtime': 381.0768678188324, 'train/epoch_acc': 0.7899262899262899, 'train/batch_loss': 0.6763702630996704, 'train/epoch_loss': 0.5319552311733255, '_step': 2059, 'test/recall': 0.625}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.0001}",glorious-sweep-27
|
||||||
74,"{'epoch': 9, '_wandb': {'runtime': 334}, 'test/epoch_acc': 0.7555555555555555, 'train/batch_loss': 0.4391788542270661, '_step': 529, '_timestamp': 1678794572.9156363, 'test/recall': 0.813953488372093, 'test/f1-score': 0.7608695652173914, 'test/precision': 0.7142857142857143, 'test/epoch_loss': 0.5729872869120703, 'train/epoch_acc': 0.8968058968058967, 'train/epoch_loss': 0.2699748155379471, '_runtime': 338.11463618278503}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",stoic-sweep-26
|
74,"{'_step': 529, 'epoch': 9, '_wandb': {'runtime': 334}, '_runtime': 338.11463618278503, '_timestamp': 1678794572.9156363, 'test/recall': 0.813953488372093, 'test/epoch_acc': 0.7555555555555555, 'test/epoch_loss': 0.5729872869120703, 'train/epoch_acc': 0.8968058968058967, 'train/batch_loss': 0.4391788542270661, 'test/f1-score': 0.7608695652173914, 'test/precision': 0.7142857142857143, 'train/epoch_loss': 0.2699748155379471}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",stoic-sweep-26
|
||||||
75,"{'_step': 2059, 'epoch': 9, '_wandb': {'runtime': 377}, '_timestamp': 1678794222.848524, 'test/precision': 0.8478260869565217, 'train/epoch_acc': 0.9877149877149876, 'train/batch_loss': 0.025906365364789963, '_runtime': 380.8983037471771, 'test/recall': 0.8863636363636364, 'test/f1-score': 0.8666666666666666, 'test/epoch_acc': 0.8666666666666667, 'test/epoch_loss': 0.3083995895563728, 'train/epoch_loss': 0.04955068614813831}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",vibrant-sweep-25
|
75,"{'test/epoch_loss': 0.3083995895563728, '_step': 2059, '_wandb': {'runtime': 377}, '_timestamp': 1678794222.848524, 'test/recall': 0.8863636363636364, 'test/f1-score': 0.8666666666666666, 'test/precision': 0.8478260869565217, 'epoch': 9, '_runtime': 380.8983037471771, 'test/epoch_acc': 0.8666666666666667, 'train/epoch_acc': 0.9877149877149876, 'train/batch_loss': 0.025906365364789963, 'train/epoch_loss': 0.04955068614813831}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",vibrant-sweep-25
|
||||||
76,"{'train/epoch_acc': 1, 'train/batch_loss': 0.0010389955714344978, '_step': 149, 'epoch': 9, '_timestamp': 1678793829.5489533, 'test/recall': 0.9215686274509804, 'test/f1-score': 0.8867924528301887, 'test/precision': 0.8545454545454545, '_wandb': {'runtime': 340}, '_runtime': 343.4739582538605, 'test/epoch_acc': 0.8666666666666667, 'test/epoch_loss': 0.7976957665549385, 'train/epoch_loss': 0.002287556243378495}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",valiant-sweep-24
|
76,"{'test/f1-score': 0.8867924528301887, 'test/precision': 0.8545454545454545, 'test/epoch_loss': 0.7976957665549385, '_step': 149, 'epoch': 9, '_wandb': {'runtime': 340}, '_timestamp': 1678793829.5489533, 'test/recall': 0.9215686274509804, 'train/epoch_acc': 1, '_runtime': 343.4739582538605, 'test/epoch_acc': 0.8666666666666667, 'train/batch_loss': 0.0010389955714344978, 'train/epoch_loss': 0.002287556243378495}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.1}",valiant-sweep-24
|
||||||
77,"{'epoch': 9, 'test/precision': 0.8666666666666667, 'train/epoch_acc': 0.8857493857493858, 'train/epoch_loss': 0.3862068348493272, '_step': 149, '_runtime': 344.0598545074463, '_timestamp': 1678793464.5180786, 'test/recall': 0.8478260869565217, 'test/f1-score': 0.8571428571428571, 'test/epoch_acc': 0.8555555555555556, 'test/epoch_loss': 0.4112878143787384, 'train/batch_loss': 0.3762533664703369, '_wandb': {'runtime': 340}}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.001}",polished-sweep-23
|
77,"{'test/f1-score': 0.8571428571428571, 'test/precision': 0.8666666666666667, 'test/epoch_loss': 0.4112878143787384, 'train/batch_loss': 0.3762533664703369, 'train/epoch_loss': 0.3862068348493272, 'epoch': 9, '_runtime': 344.0598545074463, 'test/recall': 0.8478260869565217, 'test/epoch_acc': 0.8555555555555556, 'train/epoch_acc': 0.8857493857493858, '_step': 149, '_wandb': {'runtime': 340}, '_timestamp': 1678793464.5180786}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.001}",polished-sweep-23
|
||||||
78,"{'train/epoch_acc': 0.6756756756756757, 'train/batch_loss': 0.7007869482040405, 'train/epoch_loss': 0.6115244123215171, '_step': 529, 'epoch': 9, '_runtime': 339.41979336738586, '_timestamp': 1678793108.7606344, 'test/epoch_loss': 0.6097042110231188, '_wandb': {'runtime': 336}, 'test/recall': 0.8837209302325582, 'test/f1-score': 0.7102803738317758, 'test/epoch_acc': 0.6555555555555556, 'test/precision': 0.59375}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",clear-sweep-22
|
78,"{'_timestamp': 1678793108.7606344, 'test/recall': 0.8837209302325582, 'test/epoch_loss': 0.6097042110231188, 'train/epoch_acc': 0.6756756756756757, 'train/batch_loss': 0.7007869482040405, 'epoch': 9, '_wandb': {'runtime': 336}, '_runtime': 339.41979336738586, 'test/f1-score': 0.7102803738317758, 'test/epoch_acc': 0.6555555555555556, 'test/precision': 0.59375, 'train/epoch_loss': 0.6115244123215171, '_step': 529}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",clear-sweep-22
|
||||||
79,"{'_wandb': {'runtime': 377}, '_runtime': 381.0477261543274, '_timestamp': 1678792758.596286, 'test/recall': 0.8157894736842105, 'test/precision': 0.9393939393939394, 'train/epoch_acc': 0.9815724815724816, 'epoch': 9, 'test/f1-score': 0.8732394366197183, 'test/epoch_acc': 0.9, 'test/epoch_loss': 0.23743902287549443, 'train/batch_loss': 0.5061427354812622, 'train/epoch_loss': 0.07462231436439994, '_step': 2059}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",sage-sweep-21
|
79,"{'test/precision': 0.9393939393939394, 'train/epoch_loss': 0.07462231436439994, 'epoch': 9, '_runtime': 381.0477261543274, 'test/epoch_acc': 0.9, 'test/recall': 0.8157894736842105, 'test/f1-score': 0.8732394366197183, 'test/epoch_loss': 0.23743902287549443, 'train/epoch_acc': 0.9815724815724816, 'train/batch_loss': 0.5061427354812622, '_step': 2059, '_wandb': {'runtime': 377}, '_timestamp': 1678792758.596286}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",sage-sweep-21
|
||||||
80,"{'test/precision': 0.902439024390244, 'train/batch_loss': 0.24579545855522156, 'train/epoch_loss': 0.12095561367287976, '_step': 529, 'epoch': 9, '_runtime': 335.3731348514557, 'test/epoch_acc': 0.8555555555555556, 'test/epoch_loss': 0.28035063776705, 'train/epoch_acc': 0.9791154791154792, '_wandb': {'runtime': 331}, '_timestamp': 1678792364.5292609, 'test/recall': 0.8043478260869565, 'test/f1-score': 0.8505747126436782}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.001}",olive-sweep-20
|
80,"{'_wandb': {'runtime': 331}, '_timestamp': 1678792364.5292609, 'test/f1-score': 0.8505747126436782, 'test/precision': 0.902439024390244, 'train/epoch_acc': 0.9791154791154792, 'train/batch_loss': 0.24579545855522156, 'train/epoch_loss': 0.12095561367287976, '_step': 529, 'epoch': 9, '_runtime': 335.3731348514557, 'test/recall': 0.8043478260869565, 'test/epoch_acc': 0.8555555555555556, 'test/epoch_loss': 0.28035063776705}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 16, 'learning_rate': 0.001}",olive-sweep-20
|
||||||
81,"{'_step': 1039, 'epoch': 9, '_runtime': 340.5063774585724, 'test/precision': 0.9534883720930232, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.0077079650945961475, 'train/epoch_loss': 0.018187719287696302, '_wandb': {'runtime': 337}, '_timestamp': 1678792015.2579195, 'test/recall': 0.9111111111111112, 'test/f1-score': 0.931818181818182, 'test/epoch_acc': 0.9333333333333332, 'test/epoch_loss': 0.17397157057291932}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",autumn-sweep-19
|
81,"{'_wandb': {'runtime': 337}, 'test/recall': 0.9111111111111112, 'test/f1-score': 0.931818181818182, 'test/epoch_acc': 0.9333333333333332, 'test/precision': 0.9534883720930232, 'test/epoch_loss': 0.17397157057291932, 'epoch': 9, '_runtime': 340.5063774585724, '_timestamp': 1678792015.2579195, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.0077079650945961475, 'train/epoch_loss': 0.018187719287696302, '_step': 1039}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",autumn-sweep-19
|
||||||
82,"{'train/batch_loss': 0.4317986071109772, '_step': 1039, 'epoch': 9, 'test/recall': 0.8205128205128205, 'test/f1-score': 0.7804878048780488, 'test/epoch_acc': 0.8, 'test/epoch_loss': 0.4940012666914198, 'train/epoch_acc': 0.8218673218673218, 'train/epoch_loss': 0.4784781006542412, '_wandb': {'runtime': 344}, '_runtime': 347.40152740478516, '_timestamp': 1678791661.9692383, 'test/precision': 0.7441860465116279}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0001}",crisp-sweep-18
|
82,"{'epoch': 9, '_wandb': {'runtime': 344}, 'test/recall': 0.8205128205128205, 'train/epoch_loss': 0.4784781006542412, 'test/epoch_loss': 0.4940012666914198, 'train/epoch_acc': 0.8218673218673218, '_step': 1039, '_runtime': 347.40152740478516, '_timestamp': 1678791661.9692383, 'test/f1-score': 0.7804878048780488, 'test/epoch_acc': 0.8, 'test/precision': 0.7441860465116279, 'train/batch_loss': 0.4317986071109772}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0001}",crisp-sweep-18
|
||||||
83,"{'test/recall': 0.9090909090909092, 'test/f1-score': 0.9090909090909092, 'test/epoch_acc': 0.9111111111111112, 'test/precision': 0.9090909090909092, 'test/epoch_loss': 0.19624250796106127, '_step': 279, '_wandb': {'runtime': 335}, '_timestamp': 1678791236.6172178, 'train/epoch_acc': 0.9828009828009828, 'train/batch_loss': 0.15555259585380554, 'epoch': 9, '_runtime': 337.956387758255, 'train/epoch_loss': 0.08830470366618558}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.003}",deep-sweep-16
|
83,"{'_runtime': 337.956387758255, 'test/recall': 0.9090909090909092, 'test/f1-score': 0.9090909090909092, 'test/precision': 0.9090909090909092, 'test/epoch_loss': 0.19624250796106127, '_step': 279, '_wandb': {'runtime': 335}, '_timestamp': 1678791236.6172178, 'test/epoch_acc': 0.9111111111111112, 'train/epoch_acc': 0.9828009828009828, 'train/batch_loss': 0.15555259585380554, 'train/epoch_loss': 0.08830470366618558, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.003}",deep-sweep-16
|
||||||
84,"{'test/epoch_acc': 0.7333333333333334, 'test/precision': 0.7049180327868853, 'test/epoch_loss': 0.6228035251299541, 'train/batch_loss': 0.6377201080322266, '_runtime': 334.2993712425232, '_timestamp': 1678790886.952144, 'test/f1-score': 0.7818181818181819, 'test/recall': 0.8775510204081632, 'train/epoch_acc': 0.7493857493857494, 'train/epoch_loss': 0.6127705679478751, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 331}}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.0003}",confused-sweep-15
|
84,"{'_step': 279, '_timestamp': 1678790886.952144, 'test/f1-score': 0.7818181818181819, 'test/precision': 0.7049180327868853, 'test/epoch_loss': 0.6228035251299541, 'train/epoch_acc': 0.7493857493857494, 'train/batch_loss': 0.6377201080322266, 'epoch': 9, '_wandb': {'runtime': 331}, '_runtime': 334.2993712425232, 'test/recall': 0.8775510204081632, 'test/epoch_acc': 0.7333333333333334, 'train/epoch_loss': 0.6127705679478751}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 32, 'learning_rate': 0.0003}",confused-sweep-15
|
||||||
85,"{'_step': 529, '_wandb': {'runtime': 342}, '_timestamp': 1678790542.286384, 'test/precision': 0.7192982456140351, 'train/epoch_acc': 0.8415233415233415, 'train/batch_loss': 0.1340156048536301, 'train/epoch_loss': 0.3545121966840594, 'epoch': 9, '_runtime': 345.0617377758026, 'test/recall': 0.8541666666666666, 'test/f1-score': 0.7809523809523811, 'test/epoch_acc': 0.7444444444444445, 'test/epoch_loss': 0.6144241677390204}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.1}",ancient-sweep-14
|
85,"{'train/epoch_loss': 0.3545121966840594, '_step': 529, 'epoch': 9, '_runtime': 345.0617377758026, '_timestamp': 1678790542.286384, 'test/f1-score': 0.7809523809523811, 'train/epoch_acc': 0.8415233415233415, 'train/batch_loss': 0.1340156048536301, '_wandb': {'runtime': 342}, 'test/recall': 0.8541666666666666, 'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.7192982456140351, 'test/epoch_loss': 0.6144241677390204}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.1}",ancient-sweep-14
|
||||||
86,"{'train/epoch_acc': 0.7457002457002457, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 344}, '_runtime': 346.86587953567505, '_timestamp': 1678790183.7024884, 'test/epoch_acc': 0.7222222222222222, 'test/recall': 0.782608695652174, 'test/f1-score': 0.7422680412371134, 'test/precision': 0.7058823529411765, 'test/epoch_loss': 0.6392196734746297, 'train/batch_loss': 0.6280461549758911, 'train/epoch_loss': 0.6374555861334836}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.0003}",revived-sweep-13
|
86,"{'_step': 529, '_timestamp': 1678790183.7024884, 'test/f1-score': 0.7422680412371134, 'train/batch_loss': 0.6280461549758911, 'test/precision': 0.7058823529411765, 'test/epoch_loss': 0.6392196734746297, 'train/epoch_acc': 0.7457002457002457, 'epoch': 9, '_wandb': {'runtime': 344}, '_runtime': 346.86587953567505, 'test/recall': 0.782608695652174, 'test/epoch_acc': 0.7222222222222222, 'train/epoch_loss': 0.6374555861334836}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 16, 'learning_rate': 0.0003}",revived-sweep-13
|
||||||
87,"{'train/epoch_acc': 0.9987714987714988, 'train/batch_loss': 0.04231283441185951, '_step': 149, 'test/f1-score': 0.9010989010989012, 'test/epoch_acc': 0.9, 'test/epoch_loss': 0.24115624560250176, 'test/recall': 0.9111111111111112, 'test/precision': 0.8913043478260869, 'train/epoch_loss': 0.02119528235872196, 'epoch': 9, '_wandb': {'runtime': 348}, '_runtime': 350.9660577774048, '_timestamp': 1678789826.0085878}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.0003}",swift-sweep-12
|
87,"{'_wandb': {'runtime': 348}, '_runtime': 350.9660577774048, 'test/recall': 0.9111111111111112, 'train/epoch_acc': 0.9987714987714988, 'epoch': 9, '_timestamp': 1678789826.0085878, 'test/f1-score': 0.9010989010989012, 'test/epoch_acc': 0.9, 'test/precision': 0.8913043478260869, 'test/epoch_loss': 0.24115624560250176, 'train/batch_loss': 0.04231283441185951, 'train/epoch_loss': 0.02119528235872196, '_step': 149}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 64, 'learning_rate': 0.0003}",swift-sweep-12
|
||||||
88,"{'_step': 2059, '_runtime': 397.1281135082245, 'test/recall': 0.8333333333333334, 'test/f1-score': 0.7894736842105262, 'test/epoch_acc': 0.8222222222222223, 'test/precision': 0.75, 'test/epoch_loss': 0.5769641452365452, 'epoch': 9, '_wandb': {'runtime': 393}, '_timestamp': 1678789464.8040044, 'train/epoch_acc': 0.757985257985258, 'train/batch_loss': 0.6127220392227173, 'train/epoch_loss': 0.5840219159676929}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0001}",rosy-sweep-11
|
88,"{'test/recall': 0.8333333333333334, 'test/epoch_loss': 0.5769641452365452, 'train/batch_loss': 0.6127220392227173, 'train/epoch_loss': 0.5840219159676929, 'epoch': 9, '_wandb': {'runtime': 393}, '_timestamp': 1678789464.8040044, 'test/f1-score': 0.7894736842105262, 'test/epoch_acc': 0.8222222222222223, 'test/precision': 0.75, 'train/epoch_acc': 0.757985257985258, '_step': 2059, '_runtime': 397.1281135082245}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0001}",rosy-sweep-11
|
||||||
89,"{'train/epoch_acc': 0.9938574938574938, '_wandb': {'runtime': 352}, '_runtime': 355.46944642066956, '_timestamp': 1678789057.5684297, 'test/recall': 0.8076923076923077, 'test/f1-score': 0.8842105263157894, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.9767441860465116, 'train/epoch_loss': 0.06967324825777176, '_step': 149, 'epoch': 9, 'test/epoch_loss': 0.2696530275874668, 'train/batch_loss': 0.11590295284986496}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",deft-sweep-10
|
89,"{'epoch': 9, 'test/recall': 0.8076923076923077, 'test/f1-score': 0.8842105263157894, 'test/epoch_loss': 0.2696530275874668, 'train/epoch_acc': 0.9938574938574938, 'train/batch_loss': 0.11590295284986496, '_step': 149, '_wandb': {'runtime': 352}, '_runtime': 355.46944642066956, '_timestamp': 1678789057.5684297, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.9767441860465116, 'train/epoch_loss': 0.06967324825777176}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",deft-sweep-10
|
||||||
90,"{'train/epoch_loss': 0.6400203514450599, '_runtime': 342.3234579563141, '_timestamp': 1678788683.006292, 'test/f1-score': 0.7959183673469388, 'test/precision': 0.7090909090909091, 'test/epoch_loss': 0.6248881856600443, 'train/epoch_acc': 0.7014742014742015, 'train/batch_loss': 0.5820533037185669, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 340}, 'test/recall': 0.9069767441860463, 'test/epoch_acc': 0.7777777777777778}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.0001}",atomic-sweep-9
|
90,"{'_step': 279, '_wandb': {'runtime': 340}, '_runtime': 342.3234579563141, '_timestamp': 1678788683.006292, 'test/recall': 0.9069767441860463, 'test/f1-score': 0.7959183673469388, 'test/epoch_acc': 0.7777777777777778, 'test/precision': 0.7090909090909091, 'test/epoch_loss': 0.6248881856600443, 'train/epoch_acc': 0.7014742014742015, 'train/batch_loss': 0.5820533037185669, 'train/epoch_loss': 0.6400203514450599, 'epoch': 9}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.0001}",atomic-sweep-9
|
||||||
91,"{'train/epoch_acc': 0.7432432432432432, 'train/batch_loss': 0.3377891480922699, 'epoch': 9, '_wandb': {'runtime': 351}, 'test/epoch_acc': 0.6555555555555556, 'test/recall': 0.7954545454545454, 'test/f1-score': 0.693069306930693, 'test/precision': 0.6140350877192983, 'test/epoch_loss': 0.6175267219543457, 'train/epoch_loss': 0.5329857344855841, '_step': 1039, '_runtime': 353.4816448688507, '_timestamp': 1678788328.1196988}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.1}",cosmic-sweep-8
|
91,"{'_step': 1039, '_wandb': {'runtime': 351}, 'test/epoch_acc': 0.6555555555555556, 'test/precision': 0.6140350877192983, 'test/epoch_loss': 0.6175267219543457, 'train/epoch_acc': 0.7432432432432432, 'epoch': 9, '_runtime': 353.4816448688507, '_timestamp': 1678788328.1196988, 'test/recall': 0.7954545454545454, 'test/f1-score': 0.693069306930693, 'train/batch_loss': 0.3377891480922699, 'train/epoch_loss': 0.5329857344855841}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.1}",cosmic-sweep-8
|
||||||
92,"{'_timestamp': 1678787961.3400052, 'test/recall': 0.8536585365853658, 'test/f1-score': 0.6999999999999998, 'test/epoch_acc': 0.6666666666666667, 'test/precision': 0.5932203389830508, '_step': 2059, '_wandb': {'runtime': 390}, '_runtime': 392.4064960479736, 'train/batch_loss': 0.17200787365436554, 'train/epoch_loss': 0.5631518808058498, 'epoch': 9, 'test/epoch_loss': 0.6419186863634322, 'train/epoch_acc': 0.7186732186732187}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",lunar-sweep-7
|
92,"{'epoch': 9, '_wandb': {'runtime': 390}, '_runtime': 392.4064960479736, '_timestamp': 1678787961.3400052, 'test/f1-score': 0.6999999999999998, 'test/precision': 0.5932203389830508, 'train/epoch_loss': 0.5631518808058498, '_step': 2059, 'test/recall': 0.8536585365853658, 'test/epoch_acc': 0.6666666666666667, 'test/epoch_loss': 0.6419186863634322, 'train/epoch_acc': 0.7186732186732187, 'train/batch_loss': 0.17200787365436554}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.01}",lunar-sweep-7
|
||||||
93,"{'test/epoch_acc': 0.9, 'test/precision': 0.9090909090909092, 'test/epoch_loss': 0.24278527200222016, 'train/epoch_acc': 0.9975429975429976, 'train/epoch_loss': 0.03237721893286529, 'epoch': 9, '_timestamp': 1678787557.992564, 'test/f1-score': 0.8988764044943819, 'test/recall': 0.8888888888888888, 'train/batch_loss': 0.04353119805455208, '_step': 529, '_wandb': {'runtime': 343}, '_runtime': 345.9260220527649}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",zany-sweep-6
|
93,"{'train/epoch_acc': 0.9975429975429976, 'train/epoch_loss': 0.03237721893286529, 'epoch': 9, '_wandb': {'runtime': 343}, '_runtime': 345.9260220527649, 'test/f1-score': 0.8988764044943819, 'test/epoch_acc': 0.9, 'train/batch_loss': 0.04353119805455208, '_step': 529, '_timestamp': 1678787557.992564, 'test/recall': 0.8888888888888888, 'test/precision': 0.9090909090909092, 'test/epoch_loss': 0.24278527200222016}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",zany-sweep-6
|
||||||
94,"{'test/precision': 0.9767441860465116, 'test/epoch_loss': 0.32114719019995797, '_step': 529, '_wandb': {'runtime': 344}, '_runtime': 346.5414688587189, '_timestamp': 1678787192.9954038, 'test/recall': 0.8571428571428571, 'test/epoch_acc': 0.9111111111111112, 'train/batch_loss': 0.21811823546886444, 'train/epoch_loss': 0.2347587838000103, 'epoch': 9, 'test/f1-score': 0.9130434782608696, 'train/epoch_acc': 0.9336609336609336}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",absurd-sweep-5
|
94,"{'_step': 529, '_runtime': 346.5414688587189, 'test/f1-score': 0.9130434782608696, 'train/epoch_acc': 0.9336609336609336, 'test/epoch_loss': 0.32114719019995797, 'train/batch_loss': 0.21811823546886444, 'epoch': 9, '_wandb': {'runtime': 344}, '_timestamp': 1678787192.9954038, 'test/recall': 0.8571428571428571, 'test/epoch_acc': 0.9111111111111112, 'test/precision': 0.9767441860465116, 'train/epoch_loss': 0.2347587838000103}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.001}",absurd-sweep-5
|
||||||
95,"{'_wandb': {'runtime': 344}, '_timestamp': 1678786835.7254088, 'test/epoch_loss': 0.22436124781767527, '_step': 279, 'epoch': 9, '_runtime': 345.9469966888428, 'test/recall': 0.8461538461538461, 'test/f1-score': 0.8799999999999999, 'test/epoch_acc': 0.9, 'test/precision': 0.9166666666666666, 'train/epoch_acc': 1, 'train/batch_loss': 0.06225413456559181, 'train/epoch_loss': 0.02646600444977348}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",radiant-sweep-4
|
95,"{'_timestamp': 1678786835.7254088, 'test/f1-score': 0.8799999999999999, 'test/epoch_loss': 0.22436124781767527, 'train/epoch_loss': 0.02646600444977348, 'epoch': 9, '_wandb': {'runtime': 344}, '_runtime': 345.9469966888428, 'test/precision': 0.9166666666666666, 'train/epoch_acc': 1, 'train/batch_loss': 0.06225413456559181, '_step': 279, 'test/recall': 0.8461538461538461, 'test/epoch_acc': 0.9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",radiant-sweep-4
|
||||||
96,"{'test/epoch_acc': 0.8111111111111111, 'test/precision': 0.7446808510638298, 'train/epoch_loss': 0.45506354690476775, 'epoch': 9, '_wandb': {'runtime': 353}, '_runtime': 355.012455701828, '_timestamp': 1678786479.0865147, 'test/recall': 0.875, 'test/f1-score': 0.8045977011494252, 'test/epoch_loss': 0.4459853092829386, 'train/epoch_acc': 0.8341523341523341, '_step': 1039, 'train/batch_loss': 0.5456343293190002}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",sandy-sweep-3
|
96,"{'_wandb': {'runtime': 353}, '_runtime': 355.012455701828, 'test/recall': 0.875, 'test/f1-score': 0.8045977011494252, 'test/epoch_acc': 0.8111111111111111, 'test/precision': 0.7446808510638298, '_step': 1039, 'epoch': 9, 'train/epoch_loss': 0.45506354690476775, 'train/epoch_acc': 0.8341523341523341, 'train/batch_loss': 0.5456343293190002, '_timestamp': 1678786479.0865147, 'test/epoch_loss': 0.4459853092829386}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",sandy-sweep-3
|
||||||
97,"{'train/batch_loss': 0.026765840128064156, '_step': 529, '_runtime': 344.01046657562256, 'test/epoch_loss': 0.31915653232071134, 'train/epoch_acc': 0.9926289926289926, 'test/f1-score': 0.8450704225352113, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.9090909090909092, 'train/epoch_loss': 0.045762457081668206, 'epoch': 9, '_wandb': {'runtime': 342}, '_timestamp': 1678786112.108075, 'test/recall': 0.7894736842105263}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",pretty-sweep-2
|
97,"{'_wandb': {'runtime': 342}, '_timestamp': 1678786112.108075, 'test/recall': 0.7894736842105263, 'test/precision': 0.9090909090909092, 'test/epoch_loss': 0.31915653232071134, 'train/batch_loss': 0.026765840128064156, 'train/epoch_loss': 0.045762457081668206, '_step': 529, 'epoch': 9, '_runtime': 344.01046657562256, 'test/f1-score': 0.8450704225352113, 'test/epoch_acc': 0.8777777777777778, 'train/epoch_acc': 0.9926289926289926}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.01}",pretty-sweep-2
|
||||||
98,"{'test/f1-score': 0.379746835443038, 'test/precision': 0.42857142857142855, 'test/epoch_loss': 0.7006691349877252, 'train/epoch_acc': 0.4815724815724816, 'train/epoch_loss': 0.7011552195291262, 'epoch': 9, '_wandb': {'runtime': 357}, '_runtime': 359.66486382484436, '_timestamp': 1678785758.376562, 'test/recall': 0.3409090909090909, 'test/epoch_acc': 0.45555555555555555, 'train/batch_loss': 0.7150550484657288, '_step': 149}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.0003}",rose-sweep-1
|
98,"{'train/batch_loss': 0.7150550484657288, 'train/epoch_loss': 0.7011552195291262, '_step': 149, '_wandb': {'runtime': 357}, '_runtime': 359.66486382484436, '_timestamp': 1678785758.376562, 'test/f1-score': 0.379746835443038, 'test/precision': 0.42857142857142855, 'epoch': 9, 'test/recall': 0.3409090909090909, 'test/epoch_acc': 0.45555555555555555, 'test/epoch_loss': 0.7006691349877252, 'train/epoch_acc': 0.4815724815724816}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.0003}",rose-sweep-1
|
||||||
99,"{'_timestamp': 1678785370.5563953, 'test/recall': 0.9090909090909092, 'test/f1-score': 0.8791208791208791, 'test/precision': 0.851063829787234, 'test/epoch_loss': 0.5091631063156657, '_step': 74, '_wandb': {'runtime': 181}, '_runtime': 180.05384421348572, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.0016211483161896467, 'train/epoch_loss': 0.023103852647056927, 'epoch': 4, 'test/epoch_acc': 0.8777777777777778}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.1}",cosmic-sweep-2
|
99,"{'train/epoch_loss': 0.023103852647056927, '_step': 74, 'test/recall': 0.9090909090909092, 'test/f1-score': 0.8791208791208791, 'train/batch_loss': 0.0016211483161896467, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.851063829787234, 'test/epoch_loss': 0.5091631063156657, 'train/epoch_acc': 0.995085995085995, 'epoch': 4, '_wandb': {'runtime': 181}, '_runtime': 180.05384421348572, '_timestamp': 1678785370.5563953}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 64, 'learning_rate': 0.1}",cosmic-sweep-2
|
||||||
100,"{'test/recall': 0.9166666666666666, 'test/precision': 0.9166666666666666, 'train/batch_loss': 0.0724378228187561, '_step': 279, 'epoch': 9, '_wandb': {'runtime': 344}, '_timestamp': 1678743707.9633043, 'train/epoch_acc': 0.9828009828009828, 'train/epoch_loss': 0.11044558714297244, '_runtime': 347.11417746543884, 'test/f1-score': 0.9166666666666666, 'test/epoch_acc': 0.9111111111111112, 'test/epoch_loss': 0.2461573594146305}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.003}",ethereal-sweep-14
|
100,"{'test/f1-score': 0.9166666666666666, 'test/precision': 0.9166666666666666, 'train/epoch_acc': 0.9828009828009828, 'train/batch_loss': 0.0724378228187561, 'train/epoch_loss': 0.11044558714297244, '_step': 279, '_runtime': 347.11417746543884, 'test/recall': 0.9166666666666666, 'test/epoch_acc': 0.9111111111111112, 'test/epoch_loss': 0.2461573594146305, 'epoch': 9, '_wandb': {'runtime': 344}, '_timestamp': 1678743707.9633043}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.003}",ethereal-sweep-14
|
||||||
101,"{'_step': 149, 'epoch': 9, '_timestamp': 1678743349.8008895, 'test/epoch_acc': 0.9333333333333332, 'test/precision': 0.9545454545454546, 'test/epoch_loss': 0.16449517243438297, 'train/batch_loss': 0.05796322599053383, '_wandb': {'runtime': 346}, '_runtime': 349.69085454940796, 'test/recall': 0.9130434782608696, 'test/f1-score': 0.9333333333333332, 'train/epoch_acc': 1, 'train/epoch_loss': 0.043383844352398226}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",northern-sweep-13
|
101,"{'_step': 149, 'epoch': 9, '_wandb': {'runtime': 346}, 'test/recall': 0.9130434782608696, 'test/precision': 0.9545454545454546, 'train/batch_loss': 0.05796322599053383, 'train/epoch_loss': 0.043383844352398226, '_runtime': 349.69085454940796, '_timestamp': 1678743349.8008895, 'test/f1-score': 0.9333333333333332, 'test/epoch_acc': 0.9333333333333332, 'test/epoch_loss': 0.16449517243438297, 'train/epoch_acc': 1}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 64, 'learning_rate': 0.003}",northern-sweep-13
|
||||||
102,"{'test/epoch_acc': 0.788888888888889, '_wandb': {'runtime': 559}, '_runtime': 560.5539684295654, '_timestamp': 1678743376.8770983, 'test/recall': 0.85, 'test/f1-score': 0.7816091954022989, 'test/precision': 0.723404255319149, 'test/epoch_loss': 0.5102662573258082, 'train/epoch_acc': 0.8255528255528255, '_step': 2059, 'epoch': 9, 'train/batch_loss': 0.42048144340515137, 'train/epoch_loss': 0.40511614706651}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.001}",faithful-sweep-12
|
102,"{'_runtime': 560.5539684295654, '_timestamp': 1678743376.8770983, 'test/recall': 0.85, 'test/f1-score': 0.7816091954022989, 'train/epoch_acc': 0.8255528255528255, 'train/epoch_loss': 0.40511614706651, '_wandb': {'runtime': 559}, 'epoch': 9, 'test/epoch_acc': 0.788888888888889, 'test/precision': 0.723404255319149, 'test/epoch_loss': 0.5102662573258082, 'train/batch_loss': 0.42048144340515137, '_step': 2059}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.001}",faithful-sweep-12
|
||||||
103,"{'_wandb': {'runtime': 355}, 'test/epoch_acc': 0.8666666666666667, 'train/epoch_acc': 0.8955773955773956, 'train/epoch_loss': 0.27216847456936755, 'test/epoch_loss': 0.3378064884079827, '_step': 1039, 'epoch': 9, '_runtime': 358.3485324382782, '_timestamp': 1678742986.9751594, 'test/recall': 0.7777777777777778, 'test/f1-score': 0.8536585365853658, 'test/precision': 0.945945945945946, 'train/batch_loss': 0.5923706889152527}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0003}",zany-sweep-12
|
103,"{'_timestamp': 1678742986.9751594, 'test/recall': 0.7777777777777778, 'test/epoch_loss': 0.3378064884079827, 'epoch': 9, '_runtime': 358.3485324382782, 'test/f1-score': 0.8536585365853658, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.945945945945946, 'train/epoch_acc': 0.8955773955773956, 'train/batch_loss': 0.5923706889152527, 'train/epoch_loss': 0.27216847456936755, '_step': 1039, '_wandb': {'runtime': 355}}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0003}",zany-sweep-12
|
||||||
104,"{'test/recall': 0.9166666666666666, 'test/f1-score': 0.7415730337078651, 'test/epoch_acc': 0.7444444444444445, 'test/epoch_loss': 0.615033131175571, 'train/batch_loss': 0.6421169638633728, '_step': 1039, '_wandb': {'runtime': 358}, '_runtime': 362.78373169898987, '_timestamp': 1678742619.1453717, 'test/precision': 0.6226415094339622, 'train/epoch_acc': 0.7481572481572482, 'train/epoch_loss': 0.613342459283824, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",ruby-sweep-11
|
104,"{'test/epoch_acc': 0.7444444444444445, 'test/precision': 0.6226415094339622, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 358}, '_timestamp': 1678742619.1453717, 'test/recall': 0.9166666666666666, 'test/f1-score': 0.7415730337078651, 'train/epoch_loss': 0.613342459283824, '_runtime': 362.78373169898987, 'test/epoch_loss': 0.615033131175571, 'train/epoch_acc': 0.7481572481572482, 'train/batch_loss': 0.6421169638633728}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",ruby-sweep-11
|
||||||
105,"{'train/epoch_loss': 0.09796744051757808, '_step': 2059, 'epoch': 9, '_runtime': 531.6082515716553, '_timestamp': 1678742643.2100165, 'test/recall': 0.8076923076923077, 'test/f1-score': 0.875, 'train/epoch_acc': 0.9656019656019657, '_wandb': {'runtime': 531}, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.9545454545454546, 'test/epoch_loss': 0.3795760815549228, 'train/batch_loss': 0.07699991017580032}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.001}",fallen-sweep-10
|
105,"{'_wandb': {'runtime': 531}, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.9545454545454546, 'train/batch_loss': 0.07699991017580032, '_step': 2059, '_runtime': 531.6082515716553, '_timestamp': 1678742643.2100165, 'test/recall': 0.8076923076923077, 'test/f1-score': 0.875, 'test/epoch_loss': 0.3795760815549228, 'train/epoch_acc': 0.9656019656019657, 'train/epoch_loss': 0.09796744051757808, 'epoch': 9}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 4, 'learning_rate': 0.001}",fallen-sweep-10
|
||||||
106,"{'_step': 1039, '_wandb': {'runtime': 359}, 'test/epoch_loss': 0.2956610471010208, 'train/batch_loss': 0.1150113120675087, 'epoch': 9, '_runtime': 361.6978232860565, '_timestamp': 1678742242.6362762, 'test/recall': 0.8076923076923077, 'test/f1-score': 0.875, 'test/epoch_acc': 0.8666666666666667, 'test/precision': 0.9545454545454546, 'train/epoch_acc': 0.9103194103194104, 'train/epoch_loss': 0.24495647845821825}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.003}",rare-sweep-10
|
106,"{'test/f1-score': 0.875, 'test/precision': 0.9545454545454546, 'test/epoch_loss': 0.2956610471010208, 'train/batch_loss': 0.1150113120675087, '_step': 1039, 'epoch': 9, '_timestamp': 1678742242.6362762, 'test/recall': 0.8076923076923077, 'train/epoch_loss': 0.24495647845821825, '_wandb': {'runtime': 359}, '_runtime': 361.6978232860565, 'test/epoch_acc': 0.8666666666666667, 'train/epoch_acc': 0.9103194103194104}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.003}",rare-sweep-10
|
||||||
107,"{'train/epoch_loss': 0.310643073711407, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 471}, '_runtime': 471.6707801818848, 'train/epoch_acc': 0.8869778869778869, 'train/batch_loss': 0.14859537780284882, '_timestamp': 1678742103.7627492, 'test/recall': 0.7906976744186046, 'test/f1-score': 0.8717948717948717, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9714285714285714, 'test/epoch_loss': 0.26282389760017394}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.003}",major-sweep-9
|
107,"{'_runtime': 471.6707801818848, 'test/precision': 0.9714285714285714, '_wandb': {'runtime': 471}, '_timestamp': 1678742103.7627492, 'test/recall': 0.7906976744186046, 'test/f1-score': 0.8717948717948717, 'test/epoch_acc': 0.888888888888889, 'test/epoch_loss': 0.26282389760017394, '_step': 1039, 'epoch': 9, 'train/epoch_loss': 0.310643073711407, 'train/epoch_acc': 0.8869778869778869, 'train/batch_loss': 0.14859537780284882}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.003}",major-sweep-9
|
||||||
108,"{'test/recall': 0.6976744186046512, 'test/f1-score': 0.6451612903225806, 'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.6, 'epoch': 9, '_wandb': {'runtime': 341}, '_runtime': 344.49258494377136, '_timestamp': 1678741869.828495, 'test/epoch_loss': 0.6676742302046882, 'train/epoch_acc': 0.5921375921375921, '_step': 279, 'train/batch_loss': 0.6228023767471313, 'train/epoch_loss': 0.6766868150204932}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.0001}",spring-sweep-9
|
108,"{'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.6, 'train/epoch_acc': 0.5921375921375921, 'train/batch_loss': 0.6228023767471313, '_step': 279, '_runtime': 344.49258494377136, 'test/f1-score': 0.6451612903225806, 'test/recall': 0.6976744186046512, 'test/epoch_loss': 0.6676742302046882, 'train/epoch_loss': 0.6766868150204932, 'epoch': 9, '_wandb': {'runtime': 341}, '_timestamp': 1678741869.828495}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.0001}",spring-sweep-9
|
||||||
109,"{'_runtime': 452.4322986602783, '_timestamp': 1678741623.0662856, 'test/recall': 0.9318181818181818, 'test/f1-score': 0.9213483146067416, 'test/precision': 0.9111111111111112, 'test/epoch_loss': 0.16872049139605627, 'train/batch_loss': 0.0022799931466579437, '_step': 1039, 'train/epoch_loss': 0.02303326028314504, '_wandb': {'runtime': 451}, 'test/epoch_acc': 0.9222222222222224, 'train/epoch_acc': 0.9987714987714988, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",elated-sweep-8
|
109,"{'test/epoch_loss': 0.16872049139605627, 'train/epoch_acc': 0.9987714987714988, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 451}, '_runtime': 452.4322986602783, 'test/f1-score': 0.9213483146067416, 'test/precision': 0.9111111111111112, 'train/epoch_loss': 0.02303326028314504, '_timestamp': 1678741623.0662856, 'test/recall': 0.9318181818181818, 'test/epoch_acc': 0.9222222222222224, 'train/batch_loss': 0.0022799931466579437}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.003}",elated-sweep-8
|
||||||
110,"{'_runtime': 345.3405177593231, '_timestamp': 1678741511.9070578, 'test/epoch_acc': 0.9555555555555556, 'test/precision': 0.9761904761904762, 'test/epoch_loss': 0.2148759490913815, 'train/epoch_acc': 0.9606879606879608, 'train/batch_loss': 0.11643347889184952, 'epoch': 9, 'train/epoch_loss': 0.1359616077759049, '_wandb': {'runtime': 342}, 'test/recall': 0.9318181818181818, 'test/f1-score': 0.9534883720930232, '_step': 149}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.003}",hardy-sweep-8
|
110,"{'_step': 149, '_runtime': 345.3405177593231, 'test/f1-score': 0.9534883720930232, 'test/precision': 0.9761904761904762, 'test/epoch_loss': 0.2148759490913815, 'train/epoch_acc': 0.9606879606879608, 'epoch': 9, '_wandb': {'runtime': 342}, '_timestamp': 1678741511.9070578, 'test/recall': 0.9318181818181818, 'test/epoch_acc': 0.9555555555555556, 'train/batch_loss': 0.11643347889184952, 'train/epoch_loss': 0.1359616077759049}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.003}",hardy-sweep-8
|
||||||
111,"{'_step': 279, 'test/epoch_loss': 0.2181672462158733, 'train/epoch_acc': 1, 'train/batch_loss': 0.042314428836107254, 'test/recall': 0.8048780487804879, 'test/f1-score': 0.868421052631579, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9428571428571428, 'epoch': 9, '_wandb': {'runtime': 342}, '_runtime': 345.1732180118561, '_timestamp': 1678741156.130327, 'train/epoch_loss': 0.008645273717600824}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.1}",sweepy-sweep-7
|
111,"{'epoch': 9, '_wandb': {'runtime': 342}, '_runtime': 345.1732180118561, '_timestamp': 1678741156.130327, 'test/recall': 0.8048780487804879, 'test/epoch_acc': 0.888888888888889, 'train/epoch_acc': 1, '_step': 279, 'train/epoch_loss': 0.008645273717600824, 'test/precision': 0.9428571428571428, 'test/epoch_loss': 0.2181672462158733, 'train/batch_loss': 0.042314428836107254, 'test/f1-score': 0.868421052631579}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 32, 'learning_rate': 0.1}",sweepy-sweep-7
|
||||||
112,"{'train/batch_loss': 0.3791900873184204, '_step': 1039, '_wandb': {'runtime': 453}, '_runtime': 454.0593776702881, 'test/recall': 0.6341463414634146, 'test/precision': 0.8387096774193549, 'test/epoch_loss': 0.4768455002042982, 'train/epoch_acc': 0.8292383292383292, 'epoch': 9, '_timestamp': 1678741159.4683807, 'test/f1-score': 0.7222222222222222, 'test/epoch_acc': 0.7777777777777778, 'train/epoch_loss': 0.45283343838825274}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0001}",glorious-sweep-7
|
112,"{'_step': 1039, 'test/f1-score': 0.7222222222222222, 'test/epoch_acc': 0.7777777777777778, 'test/precision': 0.8387096774193549, 'test/epoch_loss': 0.4768455002042982, 'train/epoch_acc': 0.8292383292383292, 'train/epoch_loss': 0.45283343838825274, 'epoch': 9, '_wandb': {'runtime': 453}, '_runtime': 454.0593776702881, '_timestamp': 1678741159.4683807, 'test/recall': 0.6341463414634146, 'train/batch_loss': 0.3791900873184204}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 8, 'learning_rate': 0.0001}",glorious-sweep-7
|
||||||
113,"{'test/epoch_acc': 0.9333333333333332, 'test/precision': 0.9333333333333332, 'train/batch_loss': 0.001889266073703766, 'train/epoch_loss': 0.0030514685945077376, 'epoch': 9, '_timestamp': 1678740798.1400597, '_runtime': 348.53755164146423, 'test/recall': 0.9333333333333332, 'test/f1-score': 0.9333333333333332, 'test/epoch_loss': 0.1931780371401045, 'train/epoch_acc': 1, '_step': 149, '_wandb': {'runtime': 346}}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",rural-sweep-6
|
113,"{'test/epoch_loss': 0.1931780371401045, 'epoch': 9, '_wandb': {'runtime': 346}, 'test/f1-score': 0.9333333333333332, 'test/precision': 0.9333333333333332, 'test/epoch_acc': 0.9333333333333332, 'train/epoch_acc': 1, 'train/batch_loss': 0.001889266073703766, 'train/epoch_loss': 0.0030514685945077376, '_step': 149, '_runtime': 348.53755164146423, '_timestamp': 1678740798.1400597, 'test/recall': 0.9333333333333332}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 64, 'learning_rate': 0.01}",rural-sweep-6
|
||||||
114,"{'_step': 2059, 'epoch': 9, 'test/f1-score': 0.896551724137931, 'test/precision': 0.9285714285714286, '_wandb': {'runtime': 560}, '_runtime': 560.7404127120972, '_timestamp': 1678740696.0305526, 'test/recall': 0.8666666666666667, 'test/epoch_acc': 0.9, 'test/epoch_loss': 0.22745563416845269, 'train/epoch_acc': 0.984029484029484, 'train/batch_loss': 0.1385842263698578, 'train/epoch_loss': 0.07075482415817952}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",smart-sweep-6
|
114,"{'epoch': 9, 'test/recall': 0.8666666666666667, 'test/f1-score': 0.896551724137931, 'test/epoch_acc': 0.9, 'train/batch_loss': 0.1385842263698578, '_step': 2059, '_runtime': 560.7404127120972, '_timestamp': 1678740696.0305526, 'test/precision': 0.9285714285714286, 'test/epoch_loss': 0.22745563416845269, 'train/epoch_acc': 0.984029484029484, 'train/epoch_loss': 0.07075482415817952, '_wandb': {'runtime': 560}}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",smart-sweep-6
|
||||||
115,"{'epoch': 9, '_wandb': {'runtime': 342}, '_runtime': 345.5716743469238, 'test/epoch_acc': 0.8111111111111111, 'test/precision': 0.8636363636363636, 'train/batch_loss': 0.44296249747276306, 'train/epoch_loss': 0.5191410552225183, '_step': 529, '_timestamp': 1678740438.4959724, 'test/recall': 0.7755102040816326, 'test/f1-score': 0.8172043010752688, 'test/epoch_loss': 0.507676590151257, 'train/epoch_acc': 0.7616707616707616}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",giddy-sweep-5
|
115,"{'_runtime': 345.5716743469238, '_timestamp': 1678740438.4959724, 'test/recall': 0.7755102040816326, 'test/f1-score': 0.8172043010752688, 'train/epoch_acc': 0.7616707616707616, 'train/epoch_loss': 0.5191410552225183, 'epoch': 9, '_wandb': {'runtime': 342}, 'test/precision': 0.8636363636363636, 'test/epoch_loss': 0.507676590151257, 'train/batch_loss': 0.44296249747276306, '_step': 529, 'test/epoch_acc': 0.8111111111111111}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 16, 'learning_rate': 0.1}",giddy-sweep-5
|
||||||
116,"{'_wandb': {'runtime': 342}, '_runtime': 345.28623247146606, 'test/f1-score': 0.6842105263157895, 'train/epoch_acc': 0.8538083538083537, 'train/batch_loss': 0.4066888689994812, 'test/precision': 0.7027027027027027, 'test/epoch_loss': 0.6657861550649007, 'train/epoch_loss': 0.32492415251837314, '_step': 529, 'epoch': 9, '_timestamp': 1678740073.5443084, 'test/recall': 0.6666666666666666, 'test/epoch_acc': 0.7333333333333334}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",lilac-sweep-4
|
116,"{'_step': 529, 'epoch': 9, '_runtime': 345.28623247146606, 'test/f1-score': 0.6842105263157895, 'train/epoch_acc': 0.8538083538083537, 'train/batch_loss': 0.4066888689994812, 'train/epoch_loss': 0.32492415251837314, '_wandb': {'runtime': 342}, '_timestamp': 1678740073.5443084, 'test/recall': 0.6666666666666666, 'test/epoch_acc': 0.7333333333333334, 'test/precision': 0.7027027027027027, 'test/epoch_loss': 0.6657861550649007}","{'eps': 1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.1}",lilac-sweep-4
|
||||||
117,"{'test/recall': 0.8367346938775511, 'test/f1-score': 0.8913043478260869, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9534883720930232, 'train/epoch_acc': 0.9803439803439804, 'train/batch_loss': 0.01167443674057722, '_step': 1039, 'epoch': 9, '_timestamp': 1678740126.212114, 'test/epoch_loss': 0.2600655794143677, 'train/epoch_loss': 0.08152788232426166, '_wandb': {'runtime': 454}, '_runtime': 454.98564982414246}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",hearty-sweep-5
|
117,"{'_step': 1039, 'epoch': 9, '_wandb': {'runtime': 454}, '_runtime': 454.98564982414246, 'test/epoch_acc': 0.888888888888889, 'test/epoch_loss': 0.2600655794143677, 'train/batch_loss': 0.01167443674057722, '_timestamp': 1678740126.212114, 'test/recall': 0.8367346938775511, 'test/f1-score': 0.8913043478260869, 'test/precision': 0.9534883720930232, 'train/epoch_acc': 0.9803439803439804, 'train/epoch_loss': 0.08152788232426166}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",hearty-sweep-5
|
||||||
118,"{'epoch': 9, '_wandb': {'runtime': 354}, '_runtime': 356.9382667541504, 'test/epoch_acc': 0.788888888888889, 'train/epoch_loss': 0.5079173609724209, '_step': 1039, '_timestamp': 1678739717.8250418, 'test/recall': 0.875, 'test/f1-score': 0.7865168539325842, 'test/precision': 0.7142857142857143, 'test/epoch_loss': 0.4899995631641812, 'train/epoch_acc': 0.8144963144963144, 'train/batch_loss': 0.6180618405342102}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0001}",silvery-sweep-3
|
118,"{'train/epoch_acc': 0.8144963144963144, 'epoch': 9, '_wandb': {'runtime': 354}, '_timestamp': 1678739717.8250418, 'test/epoch_acc': 0.788888888888889, 'test/epoch_loss': 0.4899995631641812, 'train/batch_loss': 0.6180618405342102, 'train/epoch_loss': 0.5079173609724209, '_step': 1039, '_runtime': 356.9382667541504, 'test/recall': 0.875, 'test/f1-score': 0.7865168539325842, 'test/precision': 0.7142857142857143}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0001}",silvery-sweep-3
|
||||||
119,"{'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9142857142857144, 'train/batch_loss': 0.2711101472377777, 'train/epoch_loss': 0.28549219298128414, '_wandb': {'runtime': 453}, '_runtime': 454.2519624233246, '_timestamp': 1678739662.5458224, 'test/f1-score': 0.8648648648648648, 'test/epoch_loss': 0.3028925802972582, 'train/epoch_acc': 0.8968058968058967, '_step': 1039, 'epoch': 9, 'test/recall': 0.8205128205128205}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0003}",dulcet-sweep-4
|
119,"{'_wandb': {'runtime': 453}, 'test/precision': 0.9142857142857144, 'train/epoch_acc': 0.8968058968058967, 'train/batch_loss': 0.2711101472377777, 'test/epoch_loss': 0.3028925802972582, '_step': 1039, 'epoch': 9, '_runtime': 454.2519624233246, '_timestamp': 1678739662.5458224, 'test/recall': 0.8205128205128205, 'test/f1-score': 0.8648648648648648, 'test/epoch_acc': 0.888888888888889, 'train/epoch_loss': 0.28549219298128414}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.99, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 8, 'learning_rate': 0.0003}",dulcet-sweep-4
|
||||||
120,"{'_timestamp': 1678739351.1315958, 'test/f1-score': 0.6451612903225806, 'test/epoch_acc': 0.6333333333333333, 'test/epoch_loss': 0.6651701913939582, 'train/epoch_acc': 0.6928746928746928, 'train/batch_loss': 0.6685948967933655, '_step': 529, 'epoch': 9, 'test/recall': 0.7894736842105263, 'test/precision': 0.5454545454545454, 'train/epoch_loss': 0.6479796424544707, '_wandb': {'runtime': 341}, '_runtime': 343.88807487487793}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.001}",glamorous-sweep-2
|
120,"{'train/epoch_loss': 0.6479796424544707, '_step': 529, '_runtime': 343.88807487487793, 'test/f1-score': 0.6451612903225806, 'test/epoch_acc': 0.6333333333333333, 'test/precision': 0.5454545454545454, 'test/epoch_loss': 0.6651701913939582, 'train/epoch_acc': 0.6928746928746928, 'train/batch_loss': 0.6685948967933655, 'epoch': 9, '_wandb': {'runtime': 341}, '_timestamp': 1678739351.1315958, 'test/recall': 0.7894736842105263}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.999, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.001}",glamorous-sweep-2
|
||||||
121,"{'train/batch_loss': 0.6510805487632751, '_step': 1039, 'epoch': 9, '_wandb': {'runtime': 469}, 'test/f1-score': 0.7608695652173914, 'test/epoch_loss': 0.6144020875295003, 'train/epoch_acc': 0.7542997542997543, '_runtime': 469.65283608436584, '_timestamp': 1678739200.083605, 'test/recall': 0.875, 'test/epoch_acc': 0.7555555555555555, 'test/precision': 0.6730769230769231, 'train/epoch_loss': 0.6267796501480684}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",hopeful-sweep-3
|
121,"{'_runtime': 469.65283608436584, 'epoch': 9, '_wandb': {'runtime': 469}, 'test/recall': 0.875, 'test/f1-score': 0.7608695652173914, 'test/epoch_acc': 0.7555555555555555, 'test/precision': 0.6730769230769231, 'test/epoch_loss': 0.6144020875295003, 'train/epoch_acc': 0.7542997542997543, '_step': 1039, '_timestamp': 1678739200.083605, 'train/batch_loss': 0.6510805487632751, 'train/epoch_loss': 0.6267796501480684}","{'eps': 0.1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",hopeful-sweep-3
|
||||||
122,"{'_wandb': {'runtime': 353}, '_timestamp': 1678738994.027642, 'test/recall': 0.8409090909090909, 'test/precision': 0.8409090909090909, 'test/epoch_loss': 0.3028163850307465, 'train/batch_loss': 0.0980801358819008, '_step': 279, '_runtime': 357.5890119075775, 'test/f1-score': 0.8409090909090909, 'test/epoch_acc': 0.8444444444444444, 'train/epoch_acc': 0.9975429975429976, 'train/epoch_loss': 0.03763626415181805, 'epoch': 9}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",lunar-sweep-1
|
122,"{'test/precision': 0.8409090909090909, 'train/epoch_acc': 0.9975429975429976, 'train/batch_loss': 0.0980801358819008, '_step': 279, '_wandb': {'runtime': 353}, '_runtime': 357.5890119075775, 'test/f1-score': 0.8409090909090909, 'test/epoch_acc': 0.8444444444444444, 'train/epoch_loss': 0.03763626415181805, 'epoch': 9, '_timestamp': 1678738994.027642, 'test/recall': 0.8409090909090909, 'test/epoch_loss': 0.3028163850307465}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 5, 'batch_size': 32, 'learning_rate': 0.003}",lunar-sweep-1
|
||||||
123,"{'test/f1-score': 0.7157894736842105, 'test/precision': 0.5964912280701754, 'train/epoch_acc': 0.6658476658476659, '_step': 2059, '_runtime': 529.6096863746643, '_timestamp': 1678738720.9443874, 'test/epoch_acc': 0.7000000000000001, 'test/epoch_loss': 0.5541173484590318, 'train/batch_loss': 0.7896618843078613, 'train/epoch_loss': 0.618659178367118, 'epoch': 9, '_wandb': {'runtime': 529}, 'test/recall': 0.8947368421052632}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.1}",stoic-sweep-2
|
123,"{'test/f1-score': 0.7157894736842105, 'test/epoch_loss': 0.5541173484590318, '_timestamp': 1678738720.9443874, 'test/recall': 0.8947368421052632, 'test/epoch_acc': 0.7000000000000001, 'test/precision': 0.5964912280701754, '_step': 2059, 'epoch': 9, '_wandb': {'runtime': 529}, '_runtime': 529.6096863746643, 'train/epoch_acc': 0.6658476658476659, 'train/batch_loss': 0.7896618843078613, 'train/epoch_loss': 0.618659178367118}","{'eps': 1e-08, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.9, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.1}",stoic-sweep-2
|
||||||
124,"{'test/recall': 0.6578947368421053, 'test/f1-score': 0.7575757575757577, 'test/epoch_acc': 0.8222222222222223, 'test/precision': 0.8928571428571429, 'test/epoch_loss': 0.4269479903909895, 'train/epoch_loss': 0.016353931551580648, '_step': 529, 'epoch': 9, '_wandb': {'runtime': 353}, '_runtime': 355.4184715747833, '_timestamp': 1678738469.1834886, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.0014543599681928754}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0001}",dark-sweep-2
|
124,"{'train/epoch_loss': 0.016353931551580648, 'epoch': 9, '_wandb': {'runtime': 353}, '_runtime': 355.4184715747833, '_timestamp': 1678738469.1834886, 'test/recall': 0.6578947368421053, 'train/epoch_acc': 0.995085995085995, 'train/batch_loss': 0.0014543599681928754, '_step': 529, 'test/f1-score': 0.7575757575757577, 'test/epoch_acc': 0.8222222222222223, 'test/precision': 0.8928571428571429, 'test/epoch_loss': 0.4269479903909895}","{'eps': 1e-08, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 16, 'learning_rate': 0.0001}",dark-sweep-2
|
||||||
125,"{'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.8780487804878049, 'test/epoch_loss': 0.40116495291392007, '_step': 1039, 'epoch': 9, '_runtime': 384.5172441005707, '_timestamp': 1678738101.018471, 'test/f1-score': 0.8470588235294119, 'train/batch_loss': 0.31195682287216187, 'train/epoch_loss': 0.3623260387038716, '_wandb': {'runtime': 381}, 'test/recall': 0.8181818181818182, 'train/epoch_acc': 0.8673218673218673}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",trim-sweep-1
|
125,"{'_wandb': {'runtime': 381}, '_timestamp': 1678738101.018471, 'test/f1-score': 0.8470588235294119, 'test/epoch_acc': 0.8555555555555556, 'test/epoch_loss': 0.40116495291392007, 'epoch': 9, '_runtime': 384.5172441005707, 'test/recall': 0.8181818181818182, 'test/precision': 0.8780487804878049, 'train/epoch_acc': 0.8673218673218673, 'train/batch_loss': 0.31195682287216187, 'train/epoch_loss': 0.3623260387038716, '_step': 1039}","{'eps': 0.1, 'gamma': 0.5, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",trim-sweep-1
|
||||||
126,"{'train/batch_loss': 0.6653294563293457, '_wandb': {'runtime': 560}, 'test/recall': 0.9090909090909092, 'test/f1-score': 0.8602150537634408, 'test/precision': 0.8163265306122449, 'train/epoch_acc': 0.7567567567567567, 'test/epoch_loss': 0.6165981186760796, 'train/epoch_loss': 0.6107166709712448, '_step': 2059, 'epoch': 9, '_runtime': 560.7235152721405, '_timestamp': 1678738182.1088202, 'test/epoch_acc': 0.8555555555555556}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.001}",sparkling-sweep-1
|
126,"{'epoch': 9, '_runtime': 560.7235152721405, 'test/f1-score': 0.8602150537634408, 'test/precision': 0.8163265306122449, 'train/epoch_acc': 0.7567567567567567, 'train/batch_loss': 0.6653294563293457, '_step': 2059, '_wandb': {'runtime': 560}, '_timestamp': 1678738182.1088202, 'test/recall': 0.9090909090909092, 'test/epoch_acc': 0.8555555555555556, 'test/epoch_loss': 0.6165981186760796, 'train/epoch_loss': 0.6107166709712448}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.9, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 2, 'batch_size': 4, 'learning_rate': 0.001}",sparkling-sweep-1
|
||||||
127,"{'_step': 555, '_wandb': {'runtime': 118}, '_runtime': 122.13349413871764, '_timestamp': 1678737059.0375042, 'test/recall': 0.6818181818181818, 'test/epoch_acc': 0.6555555555555556, 'test/precision': 0.6382978723404256, 'test/epoch_loss': 0.6796493821673923, 'train/epoch_acc': 0.5515970515970516, 'train/batch_loss': 0.6759337782859802, 'epoch': 1, 'test/f1-score': 0.6593406593406593, 'train/epoch_loss': 0.6851893525744539}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0003}",serene-sweep-1
|
127,"{'_step': 555, 'epoch': 1, '_timestamp': 1678737059.0375042, 'test/recall': 0.6818181818181818, 'test/epoch_acc': 0.6555555555555556, 'test/precision': 0.6382978723404256, '_wandb': {'runtime': 118}, '_runtime': 122.13349413871764, 'test/f1-score': 0.6593406593406593, 'test/epoch_loss': 0.6796493821673923, 'train/epoch_acc': 0.5515970515970516, 'train/batch_loss': 0.6759337782859802, 'train/epoch_loss': 0.6851893525744539}","{'eps': 1, 'gamma': 0.1, 'epochs': 10, 'beta_one': 0.99, 'beta_two': 0.5, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.0003}",serene-sweep-1
|
||||||
128,"{'_runtime': 456.3002746105194, 'test/f1-score': 0.8888888888888888, 'test/epoch_loss': 0.45068282733360926, 'train/batch_loss': 0.003167948452755809, '_wandb': {'runtime': 455}, 'epoch': 9, 'test/epoch_acc': 0.8777777777777778, '_step': 1159, 'test/recall': 0.8461538461538461, 'test/batch_loss': 0.1311825066804886, 'train/epoch_loss': 0.032788554922144414, '_timestamp': 1678734250.8076646, 'train/epoch_acc': 0.9914004914004914, 'test/precision': 0.9361702127659576}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.003}",super-sweep-10
|
128,"{'_wandb': {'runtime': 455}, 'train/epoch_acc': 0.9914004914004914, 'test/precision': 0.9361702127659576, 'test/batch_loss': 0.1311825066804886, 'train/epoch_loss': 0.032788554922144414, '_runtime': 456.3002746105194, '_timestamp': 1678734250.8076646, 'test/f1-score': 0.8888888888888888, 'train/batch_loss': 0.003167948452755809, '_step': 1159, 'test/recall': 0.8461538461538461, 'test/epoch_loss': 0.45068282733360926, 'epoch': 9, 'test/epoch_acc': 0.8777777777777778}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.003}",super-sweep-10
|
||||||
129,"{'train/epoch_acc': 0.687960687960688, 'train/epoch_loss': 0.5984233345387902, '_runtime': 564.230875492096, '_timestamp': 1678733784.6976814, 'test/epoch_acc': 0.7111111111111111, 'test/epoch_loss': 0.5302444166607327, 'epoch': 9, '_wandb': {'runtime': 563}, 'test/recall': 0.7674418604651163, '_step': 2289, 'train/batch_loss': 0.3260266184806824, 'test/f1-score': 0.7173913043478259, 'test/precision': 0.673469387755102, 'test/batch_loss': 0.9658783674240112}","{'gamma': 0.1, 'epochs': 10, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",distinctive-sweep-9
|
129,"{'_wandb': {'runtime': 563}, '_runtime': 564.230875492096, 'test/f1-score': 0.7173913043478259, 'test/batch_loss': 0.9658783674240112, 'train/epoch_loss': 0.5984233345387902, '_step': 2289, 'test/precision': 0.673469387755102, 'test/recall': 0.7674418604651163, 'train/epoch_acc': 0.687960687960688, 'train/batch_loss': 0.3260266184806824, 'epoch': 9, 'test/epoch_acc': 0.7111111111111111, 'test/epoch_loss': 0.5302444166607327, '_timestamp': 1678733784.6976814}","{'gamma': 0.1, 'epochs': 10, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",distinctive-sweep-9
|
||||||
130,"{'train/batch_loss': 0.007875862531363964, 'train/epoch_loss': 0.1743801347293527, 'test/epoch_acc': 0.9333333333333332, 'test/precision': 1, 'test/batch_loss': 0.1419784128665924, '_step': 2289, '_runtime': 527.6160025596619, 'test/recall': 0.8636363636363636, 'test/f1-score': 0.9268292682926828, 'test/epoch_loss': 0.17092165086004468, 'train/epoch_acc': 0.9496314496314496, 'epoch': 9, '_wandb': {'runtime': 527}, '_timestamp': 1678733210.1129615}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.0003}",winter-sweep-8
|
130,"{'_step': 2289, 'test/f1-score': 0.9268292682926828, '_timestamp': 1678733210.1129615, 'test/epoch_acc': 0.9333333333333332, 'test/epoch_loss': 0.17092165086004468, 'epoch': 9, 'train/batch_loss': 0.007875862531363964, 'train/epoch_loss': 0.1743801347293527, 'test/precision': 1, 'test/batch_loss': 0.1419784128665924, 'train/epoch_acc': 0.9496314496314496, '_wandb': {'runtime': 527}, '_runtime': 527.6160025596619, 'test/recall': 0.8636363636363636}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.0003}",winter-sweep-8
|
||||||
131,"{'epoch': 9, 'test/precision': 1, 'train/batch_loss': 0.04383014515042305, 'test/batch_loss': 0.27116066217422485, 'train/epoch_loss': 0.07730489082323246, 'test/epoch_acc': 0.9222222222222224, 'test/epoch_loss': 0.21558621691332924, 'train/epoch_acc': 0.9791154791154792, '_step': 1159, '_wandb': {'runtime': 452}, '_runtime': 453.52900218963623, '_timestamp': 1678732673.1225052, 'test/recall': 0.8292682926829268, 'test/f1-score': 0.9066666666666668}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",stilted-sweep-7
|
131,"{'test/f1-score': 0.9066666666666668, '_runtime': 453.52900218963623, 'test/recall': 0.8292682926829268, 'test/precision': 1, 'test/batch_loss': 0.27116066217422485, '_step': 1159, '_wandb': {'runtime': 452}, 'test/epoch_loss': 0.21558621691332924, 'train/epoch_loss': 0.07730489082323246, 'epoch': 9, '_timestamp': 1678732673.1225052, 'test/epoch_acc': 0.9222222222222224, 'train/epoch_acc': 0.9791154791154792, 'train/batch_loss': 0.04383014515042305}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.001}",stilted-sweep-7
|
||||||
132,"{'_step': 2289, 'test/batch_loss': 0.4716488718986511, 'test/epoch_loss': 0.6190193812052409, 'test/precision': 0.6538461538461539, 'train/epoch_acc': 0.7272727272727273, 'train/epoch_loss': 0.5549268187263967, '_runtime': 561.7993631362915, 'test/recall': 0.7555555555555555, 'test/f1-score': 0.7010309278350516, 'test/epoch_acc': 0.6777777777777778, 'epoch': 9, '_wandb': {'runtime': 561}, 'train/batch_loss': 0.48304444551467896, '_timestamp': 1678732212.5530572}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",summer-sweep-6
|
132,"{'_timestamp': 1678732212.5530572, 'test/f1-score': 0.7010309278350516, 'test/epoch_acc': 0.6777777777777778, 'epoch': 9, 'test/batch_loss': 0.4716488718986511, 'train/batch_loss': 0.48304444551467896, '_step': 2289, '_wandb': {'runtime': 561}, '_runtime': 561.7993631362915, 'test/precision': 0.6538461538461539, 'test/recall': 0.7555555555555555, 'test/epoch_loss': 0.6190193812052409, 'train/epoch_acc': 0.7272727272727273, 'train/epoch_loss': 0.5549268187263967}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'adam', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.01}",summer-sweep-6
|
||||||
133,"{'_step': 1159, '_wandb': {'runtime': 453}, '_timestamp': 1678731639.156168, 'test/precision': 0.945945945945946, 'test/f1-score': 0.813953488372093, 'epoch': 9, '_runtime': 454.3645238876343, 'test/recall': 0.7142857142857143, 'test/epoch_acc': 0.8222222222222223, 'test/batch_loss': 0.5068956017494202, 'test/epoch_loss': 0.4936415394147237, 'train/epoch_loss': 0.5186349417126442, 'train/epoch_acc': 0.8218673218673218, 'train/batch_loss': 0.4434223175048828}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0001}",different-sweep-5
|
133,"{'test/epoch_acc': 0.8222222222222223, 'test/batch_loss': 0.5068956017494202, 'train/epoch_loss': 0.5186349417126442, '_step': 1159, '_wandb': {'runtime': 453}, 'test/f1-score': 0.813953488372093, 'test/epoch_loss': 0.4936415394147237, 'train/batch_loss': 0.4434223175048828, 'test/recall': 0.7142857142857143, 'test/precision': 0.945945945945946, 'train/epoch_acc': 0.8218673218673218, 'epoch': 9, '_runtime': 454.3645238876343, '_timestamp': 1678731639.156168}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0001}",different-sweep-5
|
||||||
134,"{'_step': 1159, '_wandb': {'runtime': 453}, '_runtime': 454.26038885116577, 'test/epoch_loss': 0.5482642173767089, 'test/precision': 0.825, 'test/batch_loss': 0.5159374475479126, 'train/epoch_acc': 0.812039312039312, 'train/batch_loss': 0.5655931830406189, 'test/f1-score': 0.8354430379746836, 'test/epoch_acc': 0.8555555555555556, 'train/epoch_loss': 0.5429200196149016, 'epoch': 9, '_timestamp': 1678731176.111379, 'test/recall': 0.8461538461538461}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",wise-sweep-4
|
134,"{'_wandb': {'runtime': 453}, '_runtime': 454.26038885116577, 'test/batch_loss': 0.5159374475479126, 'test/epoch_loss': 0.5482642173767089, '_step': 1159, 'epoch': 9, 'train/batch_loss': 0.5655931830406189, '_timestamp': 1678731176.111379, 'test/f1-score': 0.8354430379746836, 'test/epoch_acc': 0.8555555555555556, 'test/precision': 0.825, 'train/epoch_acc': 0.812039312039312, 'train/epoch_loss': 0.5429200196149016, 'test/recall': 0.8461538461538461}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 2, 'batch_size': 8, 'learning_rate': 0.0001}",wise-sweep-4
|
||||||
135,"{'epoch': 9, '_wandb': {'runtime': 528}, 'test/recall': 0.775, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.9393939393939394, 'test/batch_loss': 1.7588363885879517, 'train/epoch_loss': 0.02060394324720534, '_step': 2289, '_runtime': 528.9760706424713, 'test/f1-score': 0.8493150684931509, '_timestamp': 1678730714.7711067, 'train/epoch_acc': 0.9963144963144964, 'train/batch_loss': 0.00470334617421031, 'test/epoch_loss': 0.24194780117250048}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.003}",misty-sweep-3
|
135,"{'test/batch_loss': 1.7588363885879517, 'train/batch_loss': 0.00470334617421031, 'train/epoch_loss': 0.02060394324720534, '_step': 2289, 'epoch': 9, 'test/f1-score': 0.8493150684931509, 'train/epoch_acc': 0.9963144963144964, '_runtime': 528.9760706424713, 'test/epoch_acc': 0.8777777777777778, 'test/precision': 0.9393939393939394, 'test/epoch_loss': 0.24194780117250048, '_wandb': {'runtime': 528}, '_timestamp': 1678730714.7711067, 'test/recall': 0.775}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 4, 'learning_rate': 0.003}",misty-sweep-3
|
||||||
136,"{'test/f1-score': 0.7536231884057972, 'test/epoch_acc': 0.8111111111111111, '_step': 1159, '_wandb': {'runtime': 454}, 'test/batch_loss': 0.455120325088501, 'test/epoch_loss': 0.4792341656155056, 'train/batch_loss': 0.5347514748573303, 'epoch': 9, 'train/epoch_acc': 0.8329238329238329, 'test/recall': 0.6842105263157895, '_timestamp': 1678730177.1362092, 'test/precision': 0.8387096774193549, 'train/epoch_loss': 0.42904984072326735, '_runtime': 455.41485929489136}","{'gamma': 0.1, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",unique-sweep-2
|
136,"{'test/batch_loss': 0.455120325088501, 'train/batch_loss': 0.5347514748573303, 'test/precision': 0.8387096774193549, 'train/epoch_acc': 0.8329238329238329, '_runtime': 455.41485929489136, 'test/recall': 0.6842105263157895, 'test/epoch_acc': 0.8111111111111111, 'test/f1-score': 0.7536231884057972, 'train/epoch_loss': 0.42904984072326735, 'epoch': 9, '_wandb': {'runtime': 454}, '_timestamp': 1678730177.1362092, '_step': 1159, 'test/epoch_loss': 0.4792341656155056}","{'gamma': 0.1, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 3, 'batch_size': 8, 'learning_rate': 0.0003}",unique-sweep-2
|
||||||
137,"{'test/precision': 0.9047619047619048, 'train/epoch_acc': 0.9901719901719902, 'test/recall': 0.8636363636363636, 'test/epoch_acc': 0.888888888888889, 'test/batch_loss': 2.5320074558258057, 'test/epoch_loss': 0.5442472649919283, 'train/epoch_loss': 0.024021292951151657, '_wandb': {'runtime': 527}, 'test/f1-score': 0.8837209302325582, 'epoch': 9, '_runtime': 528.4356484413147, '_timestamp': 1678729705.2001765, 'train/batch_loss': 0.005740344058722258, '_step': 2289}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.003}",polar-sweep-1
|
137,"{'epoch': 9, '_wandb': {'runtime': 527}, 'test/recall': 0.8636363636363636, 'test/batch_loss': 2.5320074558258057, 'train/epoch_acc': 0.9901719901719902, 'train/batch_loss': 0.005740344058722258, 'train/epoch_loss': 0.024021292951151657, '_step': 2289, 'test/epoch_acc': 0.888888888888889, 'test/precision': 0.9047619047619048, 'test/epoch_loss': 0.5442472649919283, '_runtime': 528.4356484413147, '_timestamp': 1678729705.2001765, 'test/f1-score': 0.8837209302325582}","{'gamma': 0.5, 'epochs': 10, 'optimizer': 'sgd', 'step_size': 7, 'batch_size': 4, 'learning_rate': 0.003}",polar-sweep-1
|
||||||
|
|||||||
|
File diff suppressed because one or more lines are too long
@ -29,7 +29,16 @@
|
|||||||
"execution_count": 1,
|
"execution_count": 1,
|
||||||
"id": "b88ce481",
|
"id": "b88ce481",
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"outputs": [],
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"/home/zenon/.local/share/miniconda3/lib/python3.7/site-packages/requests/__init__.py:104: RequestsDependencyWarning: urllib3 (1.26.13) or chardet (5.1.0)/charset_normalizer (2.0.4) doesn't match a supported version!\n",
|
||||||
|
" RequestsDependencyWarning)\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"import torch\n",
|
"import torch\n",
|
||||||
"import torch.nn as nn\n",
|
"import torch.nn as nn\n",
|
||||||
@ -132,7 +141,7 @@
|
|||||||
"class_names = dataset.classes\n",
|
"class_names = dataset.classes\n",
|
||||||
"\n",
|
"\n",
|
||||||
"num_epochs = 50\n",
|
"num_epochs = 50\n",
|
||||||
"batch_size = 4"
|
"batch_size = 64"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
|
|||||||
@ -95,9 +95,10 @@ def classify(resnet_path, img):
|
|||||||
batch = img.unsqueeze(0)
|
batch = img.unsqueeze(0)
|
||||||
|
|
||||||
# Do inference
|
# Do inference
|
||||||
providers = [('CUDAExecutionProvider', {
|
#providers = [('CUDAExecutionProvider',{
|
||||||
"cudnn_conv_algo_search": "DEFAULT"
|
# "cudnn_conv_algo_search": "DEFAULT"
|
||||||
}), 'CPUExecutionProvider']
|
#}), 'CPUExecutionProvider']
|
||||||
|
providers = ['CPUExecutionProvider']
|
||||||
session = onnxruntime.InferenceSession(resnet_path, providers=providers)
|
session = onnxruntime.InferenceSession(resnet_path, providers=providers)
|
||||||
|
|
||||||
outname = [i.name for i in session.get_outputs()]
|
outname = [i.name for i in session.get_outputs()]
|
||||||
@ -184,9 +185,10 @@ def get_boxes(yolo_path, image):
|
|||||||
img['image'] = img['image'].unsqueeze(0)
|
img['image'] = img['image'].unsqueeze(0)
|
||||||
|
|
||||||
# Do inference
|
# Do inference
|
||||||
providers = [('CUDAExecutionProvider', {
|
#providers = [('CUDAExecutionProvider',{
|
||||||
"cudnn_conv_algo_search": "DEFAULT"
|
# "cudnn_conv_algo_search": "DEFAULT"
|
||||||
}), 'CPUExecutionProvider']
|
#}), 'CPUExecutionProvider']
|
||||||
|
providers = ['CPUExecutionProvider']
|
||||||
session = onnxruntime.InferenceSession(yolo_path, providers=providers)
|
session = onnxruntime.InferenceSession(yolo_path, providers=providers)
|
||||||
|
|
||||||
outname = [i.name for i in session.get_outputs()]
|
outname = [i.name for i in session.get_outputs()]
|
||||||
@ -204,6 +206,7 @@ def get_boxes(yolo_path, image):
|
|||||||
|
|
||||||
# Apply NMS to results
|
# Apply NMS to results
|
||||||
preds_nms = apply_nms([outs])[0]
|
preds_nms = apply_nms([outs])[0]
|
||||||
|
#preds_nms = outs
|
||||||
|
|
||||||
# Convert boxes from resized img to original img
|
# Convert boxes from resized img to original img
|
||||||
xyxy_boxes = preds_nms[:, [1, 2, 3, 4]] # xmin, ymin, xmax, ymax
|
xyxy_boxes = preds_nms[:, [1, 2, 3, 4]] # xmin, ymin, xmax, ymax
|
||||||
|
|||||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
Binary file not shown.
Binary file not shown.
@ -79,6 +79,8 @@
|
|||||||
\newacronym{resnet}{ResNet}{Residual Neural Network}
|
\newacronym{resnet}{ResNet}{Residual Neural Network}
|
||||||
\newacronym{cnn}{CNN}{Convolutional Neural Network}
|
\newacronym{cnn}{CNN}{Convolutional Neural Network}
|
||||||
\newacronym{sgd}{SGD}{Stochastic Gradient Descent}
|
\newacronym{sgd}{SGD}{Stochastic Gradient Descent}
|
||||||
|
\newacronym{roc}{ROC}{Receiver Operating Characteristic}
|
||||||
|
\newacronym{auc}{AUC}{Area Under the Curve}
|
||||||
|
|
||||||
\begin{document}
|
\begin{document}
|
||||||
|
|
||||||
@ -294,6 +296,135 @@ for the \emph{Plant} class.
|
|||||||
\label{fig:yolo-ap}
|
\label{fig:yolo-ap}
|
||||||
\end{figure}
|
\end{figure}
|
||||||
|
|
||||||
|
\subsection{Hyper-parameter Optimization}
|
||||||
|
\label{ssec:yolo-hyp-opt}
|
||||||
|
|
||||||
|
To further improve the object detection performance, we perform
|
||||||
|
hyper-parameter optimization using a genetic algorithm. Evolution of
|
||||||
|
the hyper-parameters starts from the initial 30 default values
|
||||||
|
provided by the authors of YOLO. Of those 30 values, 26 are allowed to
|
||||||
|
mutate. During each generation, there is an 80\% chance that a
|
||||||
|
mutation occurs with a variance of 0.04. To determine which generation
|
||||||
|
should be the parent of the new mutation, all previous generations are
|
||||||
|
ordered by fitness in decreasing order. At most five top generations
|
||||||
|
are selected and one of them is chosen at random. Better generations
|
||||||
|
have a higher chance of being selected as the selection is weighted by
|
||||||
|
fitness. The parameters of that chosen generation are then mutated
|
||||||
|
with the aforementioned probability and variance. Each generation is
|
||||||
|
trained for three epochs and the fitness of the best epoch is
|
||||||
|
recorded.
|
||||||
|
|
||||||
|
In total, we ran 87 iterations of which the 34\textsuperscript{th}
|
||||||
|
generation provides the best fitness of 0.6076. Due to time
|
||||||
|
constraints, it was not possible to train each generation for more
|
||||||
|
epochs or to run more iterations in total. We assume that the
|
||||||
|
performance of the first few epochs is a reasonable proxy for model
|
||||||
|
performance overall. The optimized version of the object detection
|
||||||
|
model is then trained for 70 epochs using the parameters of the
|
||||||
|
34\textsuperscript{th} generation.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/model_fitness_final.pdf}
|
||||||
|
\caption[Optimized object detection fitness per epoch.]{Object
|
||||||
|
detection model fitness for each epoch calculated as in
|
||||||
|
equation~\ref{eq:fitness}. The vertical gray line at 27 marks the
|
||||||
|
epoch with the highest fitness of 0.6172.}
|
||||||
|
\label{fig:hyp-opt-fitness}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
Figure~\ref{fig:hyp-opt-fitness} shows the model's fitness during
|
||||||
|
training for each epoch. After the highest fitness of 0.6172 at epoch
|
||||||
|
27, the performance quickly declines and shows that further training
|
||||||
|
would likely not yield improved results. The model converges to its
|
||||||
|
highest fitness much earlier than the non-optimized version discussed
|
||||||
|
in section~\ref{ssec:yolo-training-phase}, which indicates that the
|
||||||
|
adjusted parameters provide a better starting point in general.
|
||||||
|
Furthermore, the maximum fitness is 0.74\% higher than in the
|
||||||
|
non-optimized version.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/precision_recall_final.pdf}
|
||||||
|
\caption[Hyper-parameter optimized object detection precision and
|
||||||
|
recall during training.]{Overall precision and recall during
|
||||||
|
training for each epoch of the optimized model. The vertical gray
|
||||||
|
line at 27 marks the epoch with the highest fitness.}
|
||||||
|
\label{fig:hyp-opt-prec-rec}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
Figure~\ref{fig:hyp-opt-prec-rec} shows precision and recall for the
|
||||||
|
optimized model during training. Similarly to the non-optimized model
|
||||||
|
from figure~\ref{fig:prec-rec}, both metrics do not change materially
|
||||||
|
during training. Precision is slightly higher than in the
|
||||||
|
non-optimized version and recall hovers at the same levels.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/val_box_obj_loss_final.pdf}
|
||||||
|
\caption[Hyper-parameter optimized object detection box and object
|
||||||
|
loss.]{Box and object loss measured against the validation set of
|
||||||
|
3091 images and 4092 ground truth labels. The class loss is
|
||||||
|
omitted because there is only one class in the dataset and the
|
||||||
|
loss is therefore always zero.}
|
||||||
|
\label{fig:hyp-opt-box-obj-loss}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
The box and object loss during training is pictured in
|
||||||
|
figure~\ref{fig:hyp-opt-box-obj-loss}. Both losses start from a lower
|
||||||
|
level which suggests that the initial optimized parameters allow the
|
||||||
|
model to converge quicker. The object loss exhibits a similar slope to
|
||||||
|
the non-optimized model in figure~\ref{fig:box-obj-loss}. The vertical
|
||||||
|
gray line again marks epoch 27 with the highest fitness. The box loss
|
||||||
|
reaches its lower limit at that point and the object loss starts to
|
||||||
|
increase again after epoch 27.
|
||||||
|
|
||||||
|
\begin{table}[h]
|
||||||
|
\centering
|
||||||
|
\begin{tabular}{lrrrr}
|
||||||
|
\toprule
|
||||||
|
{} & Precision & Recall & F1-score & Support \\
|
||||||
|
\midrule
|
||||||
|
Plant & 0.633358 & 0.702811 & 0.666279 & 12238.0 \\
|
||||||
|
\bottomrule
|
||||||
|
\end{tabular}
|
||||||
|
\caption{Precision, recall and F1-score for the optimized object
|
||||||
|
detection model.}
|
||||||
|
\label{tab:yolo-metrics-hyp}
|
||||||
|
\end{table}
|
||||||
|
|
||||||
|
Turning to the evaluation of the optimized model on the test dataset,
|
||||||
|
table~\ref{tab:yolo-metrics-hyp} shows precision, recall and the
|
||||||
|
F1-score for the optimized model. Comparing these metrics with the
|
||||||
|
non-optimized version from table~\ref{tab:yolo-metrics}, precision is
|
||||||
|
significantly higher by more than 8.5\%. Recall, however, is 3.5\%
|
||||||
|
lower. The F1-score is higher by more than 3.7\% which indicates that
|
||||||
|
the optimized model is better overall despite the lower recall. We
|
||||||
|
feel that the lower recall value is a suitable trade off for the
|
||||||
|
substantially higher precision considering that the non-optimized
|
||||||
|
model's precision is quite low at 0.55.
|
||||||
|
|
||||||
|
The precision-recall curves in figure~\ref{fig:yolo-ap-hyp} for the
|
||||||
|
optimized model show that the model draws looser bounding boxes than
|
||||||
|
the optimized model. The \gls{ap} for both \gls{iou} thresholds of 0.5
|
||||||
|
and 0.95 is lower indicating worse performance. It is likely that more
|
||||||
|
iterations during evolution would help increase the \gls{ap} values as
|
||||||
|
well. Even though the precision and recall values from
|
||||||
|
table~\ref{tab:yolo-metrics-hyp} are better, the \textsf{mAP}@0.5:0.95
|
||||||
|
is lower by 1.8\%.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/APpt5-pt95-final.pdf}
|
||||||
|
\caption[Hyper-parameter optimized object detection AP@0.5 and
|
||||||
|
AP@0.95.]{Precision-recall curves for \gls{iou} thresholds of 0.5
|
||||||
|
and 0.95. The \gls{ap} of a specific threshold is defined as the
|
||||||
|
area under the precision-recall curve of that threshold. The
|
||||||
|
\gls{map} across \gls{iou} thresholds from 0.5 to 0.95 in 0.05
|
||||||
|
steps \textsf{mAP}@0.5:0.95 is 0.5546.}
|
||||||
|
\label{fig:yolo-ap-hyp}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
\section{Classification}
|
\section{Classification}
|
||||||
\label{sec:resnet-eval}
|
\label{sec:resnet-eval}
|
||||||
|
|
||||||
@ -421,6 +552,89 @@ figure~\ref{fig:classifier-training-metrics}.
|
|||||||
\label{fig:resnet-hyp-results}
|
\label{fig:resnet-hyp-results}
|
||||||
\end{figure}
|
\end{figure}
|
||||||
|
|
||||||
|
Table~\ref{tab:resnet-final-hyps} lists the final hyper-parameters
|
||||||
|
which were chosen to train the improved model. In order to confirm
|
||||||
|
that the model does not suffer from overfitting or is a product of
|
||||||
|
chance due to a coincidentally advantageous train/test split, we
|
||||||
|
perform stratified $10$-fold cross validation on the dataset. Each
|
||||||
|
fold contains 90\% training and 10\% test data and was trained for 25
|
||||||
|
epochs. Figure~\ref{fig:classifier-hyp-roc} shows the performance of
|
||||||
|
the epoch with the highest F1-score of each fold as measured against
|
||||||
|
the test split. The mean \gls{roc} curve provides a robust metric for
|
||||||
|
a classifier's performance because it averages out the variability of
|
||||||
|
the evaluation. Each fold manages to achieve at least an \gls{auc} of
|
||||||
|
0.94, while the best fold reaches 0.98. The mean \gls{roc} has an
|
||||||
|
\gls{auc} of 0.96 with a standard deviation of 0.02. These results
|
||||||
|
indicate that the model is accurately predicting the correct class and
|
||||||
|
is robust against variations in the training set.
|
||||||
|
|
||||||
|
\begin{table}
|
||||||
|
\centering
|
||||||
|
\begin{tabular}{cccc}
|
||||||
|
\toprule
|
||||||
|
Optimizer & Batch Size & Learning Rate & Step Size \\
|
||||||
|
\midrule
|
||||||
|
\gls{sgd} & 64 & 0.01 & 5\\
|
||||||
|
\bottomrule
|
||||||
|
\end{tabular}
|
||||||
|
\caption[Hyper-parameters for the optimized classifier.]{Chosen
|
||||||
|
hyper-parameters for the final, improved model. The difference to
|
||||||
|
the parameters listed in Table~\ref{tab:resnet-hyps} comes as a
|
||||||
|
result of choosing \gls{sgd} over Adam. The missing four
|
||||||
|
parameters are only required for Adam and not \gls{sgd}.}
|
||||||
|
\label{tab:resnet-final-hyps}
|
||||||
|
\end{table}
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/classifier-hyp-folds-roc.pdf}
|
||||||
|
\caption[Mean \gls{roc} and variability of hyper-parameter-optimized
|
||||||
|
model.]{This plot shows the \gls{roc} curve for the epoch with the
|
||||||
|
highest F1-score of each fold as well as the \gls{auc}. To get a
|
||||||
|
less variable performance metric of the classifier, the mean
|
||||||
|
\gls{roc} curve is shown as a thick line and the variability is
|
||||||
|
shown in gray. The overall mean \gls{auc} is 0.96 with a standard
|
||||||
|
deviation of 0.02. The best-performing fold reaches an \gls{auc}
|
||||||
|
of 0.99 and the worst an \gls{auc} of 0.94. The black dashed line
|
||||||
|
indicates the performance of a classifier which picks classes at
|
||||||
|
random ($\mathrm{\gls{auc}} = 0.5$). The shapes of the \gls{roc}
|
||||||
|
curves show that the classifier performs well and is robust
|
||||||
|
against variations in the training set.}
|
||||||
|
\label{fig:classifier-hyp-roc}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
The classifier shows good performance so far, but care has to be taken
|
||||||
|
to not overfit the model to the training set. Comparing the F1-score
|
||||||
|
during training with the F1-score during testing gives insight into
|
||||||
|
when the model tries to increase its performance during training at
|
||||||
|
the expense of generalizability. Figure~\ref{fig:classifier-hyp-folds}
|
||||||
|
shows the F1-scores of each epoch and fold. The classifier converges
|
||||||
|
quickly to 1 for the training set at which point it experiences a
|
||||||
|
slight drop in generalizability. Training the model for at most five
|
||||||
|
epochs is sufficient because there are generally no improvements
|
||||||
|
afterwards. The best-performing epoch for each fold is between the
|
||||||
|
second and fourth epoch which is just before the model achieves an
|
||||||
|
F1-score of 1 on the training set.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics[width=.9\textwidth]{graphics/classifier-hyp-folds-f1.pdf}
|
||||||
|
\caption[F1-score of stratified $10$-fold cross validation.]{These
|
||||||
|
plots show the F1-score during training as well as testing for
|
||||||
|
each of the folds. The classifier converges to 1 by the third
|
||||||
|
epoch during the training phase, which might indicate
|
||||||
|
overfitting. However, the performance during testing increases
|
||||||
|
until epoch three in most cases and then stabilizes at
|
||||||
|
approximately 2-3\% lower than the best epoch. We believe that the
|
||||||
|
third, or in some cases fourth, epoch is detrimental to
|
||||||
|
performance and results in overfitting, because the model achieves
|
||||||
|
an F1-score of 1 for the training set, but that gain does not
|
||||||
|
transfer to the test set. Early stopping during training
|
||||||
|
alleviates this problem.}
|
||||||
|
\label{fig:classifier-hyp-folds}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
|
||||||
\subsection{Class Activation Maps}
|
\subsection{Class Activation Maps}
|
||||||
\label{ssec:resnet-cam}
|
\label{ssec:resnet-cam}
|
||||||
|
|
||||||
@ -438,7 +652,7 @@ One such method, \gls{cam}~\cite{zhou2015}, is a popular tool to
|
|||||||
produce visual explanations for decisions made by
|
produce visual explanations for decisions made by
|
||||||
\glspl{cnn}. Convolutional layers essentially function as object
|
\glspl{cnn}. Convolutional layers essentially function as object
|
||||||
detectors as long as no fully-connected layers perform the
|
detectors as long as no fully-connected layers perform the
|
||||||
classification. This ability to localize regions of interest which
|
classification. This ability to localize regions of interest, which
|
||||||
play a significant role in the type of class the model predicts, can
|
play a significant role in the type of class the model predicts, can
|
||||||
be retained until the last layer and used to generate activation maps
|
be retained until the last layer and used to generate activation maps
|
||||||
for the predictions.
|
for the predictions.
|
||||||
@ -567,10 +781,95 @@ the cutoff for either class.
|
|||||||
\label{fig:aggregate-ap}
|
\label{fig:aggregate-ap}
|
||||||
\end{figure}
|
\end{figure}
|
||||||
|
|
||||||
Overall, we believe that the aggregate model shows sufficient
|
\subsection{Hyper-parameter Optimization}
|
||||||
predictive performance to be deployed in the field. The detections are
|
\label{ssec:model-hyp-opt}
|
||||||
accurate, especially for potted plants, and the classification into
|
|
||||||
healthy and stressed is robust.
|
So far the metrics shown in table~\ref{tab:model-metrics} are obtained
|
||||||
|
with the non-optimized versions of both the object detection and
|
||||||
|
classification model. Hyper-parameter optimization of the classifier
|
||||||
|
led to significant model improvements, while the object detector has
|
||||||
|
improved precision but lower recall and slightly lower \gls{map}
|
||||||
|
values. To evaluate the final aggregate model which consists of the
|
||||||
|
individual optimized models, we run the same test as in
|
||||||
|
section~\ref{sec:aggregate-model}.
|
||||||
|
|
||||||
|
\begin{table}
|
||||||
|
\centering
|
||||||
|
\begin{tabular}{lrrrr}
|
||||||
|
\toprule
|
||||||
|
{} & precision & recall & f1-score & support \\
|
||||||
|
\midrule
|
||||||
|
Healthy & 0.664 & 0.640 & 0.652 & 662.0 \\
|
||||||
|
Stressed & 0.680 & 0.539 & 0.601 & 488.0 \\
|
||||||
|
micro avg & 0.670 & 0.597 & 0.631 & 1150.0 \\
|
||||||
|
macro avg & 0.672 & 0.590 & 0.626 & 1150.0 \\
|
||||||
|
weighted avg & 0.670 & 0.597 & 0.630 & 1150.0 \\
|
||||||
|
\bottomrule
|
||||||
|
\end{tabular}
|
||||||
|
\caption{Precision, recall and F1-score for the optimized aggregate
|
||||||
|
model.}
|
||||||
|
\label{tab:model-metrics-hyp}
|
||||||
|
\end{table}
|
||||||
|
|
||||||
|
Table~\ref{tab:model-metrics-hyp} shows precision, recall and F1-score
|
||||||
|
for the optimized model on the same test dataset of 640 images. All of
|
||||||
|
the metrics are significantly worse than for the non-optimized
|
||||||
|
model. Considering that the optimized classifier performs better than
|
||||||
|
the non-optimized version this is a surprising result. There are
|
||||||
|
multiple possible explanations for this behavior:
|
||||||
|
|
||||||
|
\begin{enumerate}
|
||||||
|
\item The optimized classifier has worse generalizability than the
|
||||||
|
non-optimized version.
|
||||||
|
\item The small difference in the \gls{map} values for the object
|
||||||
|
detection model result in significantly higher error rates
|
||||||
|
overall. This might be the case because a large number of plants is
|
||||||
|
not detected in the first place and/or those which are detected are
|
||||||
|
more often not classified correctly by the classifier. As mentioned
|
||||||
|
in section~\ref{ssec:yolo-hyp-opt}, running the evolution of the
|
||||||
|
hyper-parameters for more generations could better the performance
|
||||||
|
overall.
|
||||||
|
\item The test dataset is tailored to the non-optimized version and
|
||||||
|
does not provide an accurate measure of real-world performance. The
|
||||||
|
test dataset was labeled by running the individual models on the
|
||||||
|
images and taking the predicted bounding boxes and labels as a
|
||||||
|
starting point for the labeling process. If the labels were not
|
||||||
|
rigorously corrected, the dataset will allow the non-optimized model
|
||||||
|
to achieve high scores because the labels are already in line with
|
||||||
|
what it predicts. Conversely, the optimized model might get closer
|
||||||
|
to the actual ground truth, but that truth is not what is specified
|
||||||
|
by the labels to begin with. If that is the case, the evaluation of
|
||||||
|
the non-optimized model is too favorably and should be corrected
|
||||||
|
down.
|
||||||
|
\end{enumerate}
|
||||||
|
|
||||||
|
Of these three possibilities, the second and third points are the most
|
||||||
|
likely culprits. The first scenario is unlikely because the optimized
|
||||||
|
classifier has been evaluated in a cross validation setting and the
|
||||||
|
results do not lend themselves easily to such an
|
||||||
|
interpretation. Dealing with the second scenario could allow the
|
||||||
|
object detection model to perform better on its own, but would
|
||||||
|
probably not explain the big difference in performance. Scenario three
|
||||||
|
is the most likely one because the process of creating the test
|
||||||
|
dataset can lead to favorable labels for the non-optimized model.
|
||||||
|
|
||||||
|
\begin{figure}
|
||||||
|
\centering
|
||||||
|
\includegraphics{graphics/APmodel-final.pdf}
|
||||||
|
\caption[Optimized aggregate model AP@0.5 and
|
||||||
|
AP@0.95.]{Precision-recall curves for \gls{iou} thresholds of 0.5
|
||||||
|
and 0.95. The \gls{ap} of a specific threshold is defined as the
|
||||||
|
area under the precision-recall curve of that threshold. The
|
||||||
|
\gls{map} across \gls{iou} thresholds from 0.5 to 0.95 in 0.05
|
||||||
|
steps \textsf{mAP}@0.5:0.95 is 0.4426.}
|
||||||
|
\label{fig:aggregate-ap-hyp}
|
||||||
|
\end{figure}
|
||||||
|
|
||||||
|
Figure~\ref{fig:aggregate-ap-hyp} confirms the suspicions raised by
|
||||||
|
the lower metrics from table~\ref{tab:model-metrics-hyp}. More
|
||||||
|
iterations for the evolution of the object detection model would
|
||||||
|
likely have a significant effect on \gls{iou} and the confidence
|
||||||
|
values associated with the bounding boxes.
|
||||||
|
|
||||||
\backmatter
|
\backmatter
|
||||||
|
|
||||||
|
|||||||
Loading…
x
Reference in New Issue
Block a user