AntoineH/smart_augmentation
1
0
Fork 0
mirror of https://github.com/AntoineHX/smart_augmentation.git synced 2025-05-04 12:10:45 +02:00
Code Issues Projects Releases Packages Wiki Activity

Borne mag + Regularisation mag

Browse source
This commit is contained in:
Harle, Antoine (Contracteur) 2019-11-19 15:37:29 -05:00
parent f4bdd9bca5
commit 64282bda3a
10 changed files with 43 additions and 228 deletions
Download patch file Download diff file Expand all files Collapse all files

BIN
higher/res/Aug_mod(Data_augV4(Uniform-1 TF)-LeNet)-2 epochs (dataug:0)- 0 in_it.png
View file

Binary file not shown.
Side by side

Before

Width:  |  Height:  |  Size: 38 KiB

BIN
higher/res/Aug_mod(Data_augV4(Uniform-2 TF)-LeNet)-2 epochs (dataug:0)- 0 in_it.png
View file

Binary file not shown.
Side by side

Before

Width:  |  Height:  |  Size: 37 KiB

72
higher/res/log/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-2 epochs (dataug:0)- 10 in_it.json
View file

@ -1,72 +0,0 @@
{
"Accuracy": 20.8,
"Time": [
51.4427050715,
0.4778038694999971
],
"Device": "TITAN RTX",
"Param_names": [
"Identity",
"FlipUD",
"FlipLR",
"Rotate",
"TranslateX",
"TranslateY",
"ShearX",
"ShearY",
"Contrast",
"Color",
"Brightness",
"Sharpness",
"Posterize",
"Solarize"
],
"Log": [
{
"epoch": 1,
"train_loss": 2.3032476902008057,
"val_loss": 2.2924728393554688,
"acc": 11.1,
"time": 51.920508941,
"param": [
0.07925213128328323,
0.08312409371137619,
0.08779778331518173,
0.0853320062160492,
0.08577536046504974,
0.057290591299533844,
0.0774931013584137,
0.08246791362762451,
0.047001805156469345,
0.07887403666973114,
0.05897113308310509,
0.05021947622299194,
0.07581018656492233,
0.050590354949235916
]
},
{
"epoch": 2,
"train_loss": 2.171858787536621,
"val_loss": 2.078795909881592,
"acc": 20.8,
"time": 50.96490120200001,
"param": [
0.07892196625471115,
0.07488056272268295,
0.08041033148765564,
0.09144628793001175,
0.09114645421504974,
0.055715303868055344,
0.0672164335846901,
0.07994510233402252,
0.05105787515640259,
0.09191103279590607,
0.07849953323602676,
0.07014491409063339,
0.07624118775129318,
0.012463102117180824
]
}
]
}

95
higher/res/log/Aug_mod(Data_augV4(Uniform-14 TF x 2)-LeNet)-3 epochs (dataug:0)- 0 in_it.json
View file

@ -1,95 +0,0 @@
{
"Accuracy": 31.369999999999997,
"Time": [
38.67262149066667,
0.4140408795968137
],
"Device": "TITAN RTX",
"Param_names": [
"Identity",
"FlipUD",
"FlipLR",
"Rotate",
"TranslateX",
"TranslateY",
"ShearX",
"ShearY",
"Contrast",
"Color",
"Brightness",
"Sharpness",
"Posterize",
"Solarize"
],
"Log": [
{
"epoch": 1,
"train_loss": 2.2571041584014893,
"val_loss": 2.212921142578125,
"acc": 20.169999999999998,
"time": 38.788926192000005,
"param": [
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774
]
},
{
"epoch": 2,
"train_loss": 2.212834358215332,
"val_loss": 2.043567180633545,
"acc": 25.009999999999998,
"time": 38.117478509,
"param": [
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774
]
},
{
"epoch": 3,
"train_loss": 2.091825008392334,
"val_loss": 1.9359350204467773,
"acc": 31.369999999999997,
"time": 39.111459771,
"param": [
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774,
0.0714285746216774
]
}
]
}

34
higher/res/log/LeNet-3 epochs.json
View file

@ -1,34 +0,0 @@
{
"Accuracy": 39.2,
"Time": [
3.9452463850000012,
0.2891758564900622
],
"Device": "TITAN RTX",
"Log": [
{
"epoch": 0,
"train_loss": 2.109266757965088,
"val_loss": 2.1106348037719727,
"acc": 22.3,
"time": 4.312489993,
"param": null
},
{
"epoch": 1,
"train_loss": 1.7782783508300781,
"val_loss": 1.8776130676269531,
"acc": 33.76,
"time": 3.605794182000002,
"param": null
},
{
"epoch": 2,
"train_loss": 1.8152618408203125,
"val_loss": 1.6963396072387695,
"acc": 39.2,
"time": 3.9174549800000023,
"param": null
}
]
}