feat(models): save best performing model.

saeranv · May 6, 2021 · c7dc4f4 · c7dc4f4
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diff --git a/.gitignore b/.gitignore
@@ -139,6 +139,7 @@ data/ghout/
 data/traintest/
 data/traintest_small/
 data/hbjsons/
+data/
 *.sql
 *.whl
 
diff --git a/data/gh/bem_model_serialize.gh b/data/gh/bem_model_serialize.gh
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diff --git a/deeprad/model.py b/deeprad/model.py
@@ -27,25 +27,25 @@ def __init__(self, device, f1=16, k1=3):
         # TODO: add nonlinear layer?
         self.encoder = nn.Sequential(  # like the Composition layer you built
             nn.Conv2d(6, f1, k1, stride=2, padding=1),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.Conv2d(f1, f2, k1, stride=2, padding=1),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.Conv2d(f2, f3, k2),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.Conv2d(f3, f4, k2)
         )
 
         # TODO: add softmax?
         self.decoder = nn.Sequential(
             nn.ConvTranspose2d(f4, f3, k2),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.ConvTranspose2d(f3, f2, k2),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.ConvTranspose2d(f2, f1, k1, stride=2, padding=1, output_padding=1),
-            nn.ReLU(),
+            nn.LeakyReLU(),
             nn.ConvTranspose2d(f1, 3, k1, stride=2, padding=1, output_padding=1),
-            # nn.Sigmoid()
-            # nn.Tanh
+            nn.Sigmoid()
+            #nn.LeakyReLU()#,nn.Tanh
         )
 
     def forward(self, x):
@@ -96,7 +96,7 @@ def __len__(self):
 
     def __getitem__(self, idx):
         """Load image from directory given index."""
-        crop_x, crop_y = 0, 0
+        crop_x, crop_y = 0, 9
         crop_w, crop_h = 1300, 108
 
         img_loc = os.path.join(self.main_dir, self.total_imgs[idx])
@@ -108,12 +108,29 @@ def __getitem__(self, idx):
         channel_1 = Image.open(ch1_loc).convert("RGB")
         channel_2 = Image.open(ch2_loc).convert("RGB")
 
-        # Ccrop inputs
+        # Crop inputs
         image = image.crop((crop_x, crop_y, crop_x + crop_w, crop_y + crop_h))
         channel_1 = channel_1.crop((crop_x, crop_y, crop_x + crop_w, crop_y + crop_h))
         channel_2 = channel_2.crop((crop_x, crop_y, crop_x + crop_w, crop_y + crop_h))
 
+        # crop
+        # image = np.array(image)[crop_x: crop_w, crop_y : crop_h]
+        # channel_1 = np.array(channel_1)[crop_x: crop_w, crop_y: crop_h]
+        # channel_2 = np.array(channel_2)[crop_x: crop_w, crop_y: crop_h]
+
         x_in = torch.cat((self.transform(channel_1), self.transform(channel_2)), dim=0)
         y_lbl = self.transform(image)
 
+        #x_in = x_in.int()
+        #y_lbl = y_lbl.int()
+
+        del image; del channel_1; del channel_2; del img_loc; del ch1_loc; del ch2_loc
+
+        # import matplotlib.pyplot as plt
+        # y_lbl = y_lbl.permute(1, 2, 0)
+        # print(y_lbl.size())
+        # plt.imshow(y_lbl)
+        # plt.show()
+        # assert False
+
         return x_in, y_lbl
diff --git a/deeprad/traintest_utils.py b/deeprad/traintest_utils.py
@@ -53,11 +53,12 @@ def viz_loss(outputs, img_fpath, img_title='Radiation Map', xdim=10, show_plot=F
         label = label_batch[0].permute(1, 2, 0).detach().cpu().numpy()
         recon = recon_batch[0].permute(1, 2, 0).detach().cpu().numpy()
 
-        label = clean_img4rad(label) / 255.0 * 1000.0
-        recon = clean_img4rad(recon) / 255.0 * 1000.0
+        #recon = np.clip(recon, 0.0, 255.0).astype(int)
+        #label = clean_img4rad(label) / 255.0 * 1000.0
+        #recon = clean_img4rad(recon) / 255.0 * 1000.0
 
-        im = a[i, 0].imshow(label, cmap=RADCMAP, vmin=0, vmax=1000)
-        im = a[i, 1].imshow(recon, cmap=RADCMAP, vmin=0, vmax=1000)
+        im = a[i, 0].imshow(label)#, cmap=RADCMAP, vmin=0, vmax=1000)
+        im = a[i, 1].imshow(recon)#, cmap=RADCMAP, vmin=0, vmax=1000)
         clean_plot4rad(a[i], i)
 
     # left, bottom, width, height

diff --git a/models/df/result_df.pkl b/models/df/result_df.pkl
diff --git a/models/model_20210506-021606/hparams.txt b/models/model_20210506-021606/hparams.txt
@@ -0,0 +1,7 @@
+last test_loss: [0.00660582]
+test_loss: [[0.01389268]
+ [0.01008498]
+ [0.0077674 ]
+ [0.00787939]
+ [0.00660582]]
+training time: h:0 m:1 s:51
diff --git a/models/model_20210506-021606/learning_curve.jpg b/models/model_20210506-021606/learning_curve.jpg
diff --git a/models/model_20210506-021606/model_20210506-021606.pt b/models/model_20210506-021606/model_20210506-021606.pt
diff --git a/models/model_20210506-021606/test_loss_20210506-021606.jpg b/models/model_20210506-021606/test_loss_20210506-021606.jpg
diff --git a/models/model_20210506-021606/test_loss_20210506-021606.npy b/models/model_20210506-021606/test_loss_20210506-021606.npy
diff --git a/models/model_20210506-021606/train_loss_20210506-021606.jpg b/models/model_20210506-021606/train_loss_20210506-021606.jpg
diff --git a/models/model_20210506-021606/train_loss_20210506-021606.npy b/models/model_20210506-021606/train_loss_20210506-021606.npy
diff --git a/models/model_20210506-022043/hparams.txt b/models/model_20210506-022043/hparams.txt
@@ -0,0 +1,27 @@
+last test_loss: [0.00773177]
+test_loss: [[0.0122387 ]
+ [0.01925329]
+ [0.0078491 ]
+ [0.00681292]
+ [0.00626831]
+ [0.00594877]
+ [0.00793488]
+ [0.00554319]
+ [0.00509024]
+ [0.00522656]
+ [0.00500392]
+ [0.00489696]
+ [0.00436793]
+ [0.00448514]
+ [0.02440766]
+ [0.03817239]
+ [0.0262886 ]
+ [0.0252372 ]
+ [0.02446845]
+ [0.0243717 ]
+ [0.02449455]
+ [0.01615284]
+ [0.00932975]
+ [0.00845786]
+ [0.00773177]]
+training time: h:0 m:8 s:40
diff --git a/models/model_20210506-022043/learning_curve.jpg b/models/model_20210506-022043/learning_curve.jpg
diff --git a/models/model_20210506-022043/model_20210506-022043.pt b/models/model_20210506-022043/model_20210506-022043.pt
diff --git a/models/model_20210506-022043/test_loss_20210506-022043.jpg b/models/model_20210506-022043/test_loss_20210506-022043.jpg
diff --git a/models/model_20210506-022043/test_loss_20210506-022043.npy b/models/model_20210506-022043/test_loss_20210506-022043.npy
diff --git a/models/model_20210506-022043/train_loss_20210506-022043.jpg b/models/model_20210506-022043/train_loss_20210506-022043.jpg
diff --git a/models/model_20210506-022043/train_loss_20210506-022043.npy b/models/model_20210506-022043/train_loss_20210506-022043.npy
diff --git a/models/model_20210506-023823/hparams.txt b/models/model_20210506-023823/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.00513484]
+test_loss: [[0.00642225]
+ [0.00560506]
+ [0.00556434]
+ [0.00479162]
+ [0.0046627 ]
+ [0.04009283]
+ [0.04007641]
+ [0.04005576]
+ [0.04014063]
+ [0.04008703]
+ [0.04004154]
+ [0.04007852]
+ [0.04013837]
+ [0.02287525]
+ [0.00850873]
+ [0.00756035]
+ [0.00628676]
+ [0.00609663]
+ [0.00540932]
+ [0.00513484]]
+training time: h:0 m:6 s:50
diff --git a/models/model_20210506-023823/learning_curve.jpg b/models/model_20210506-023823/learning_curve.jpg
diff --git a/models/model_20210506-023823/model_20210506-023823.pt b/models/model_20210506-023823/model_20210506-023823.pt
diff --git a/models/model_20210506-023823/test_loss_20210506-023823.jpg b/models/model_20210506-023823/test_loss_20210506-023823.jpg
diff --git a/models/model_20210506-023823/test_loss_20210506-023823.npy b/models/model_20210506-023823/test_loss_20210506-023823.npy
diff --git a/models/model_20210506-023823/train_loss_20210506-023823.jpg b/models/model_20210506-023823/train_loss_20210506-023823.jpg
diff --git a/models/model_20210506-023823/train_loss_20210506-023823.npy b/models/model_20210506-023823/train_loss_20210506-023823.npy
diff --git a/models/model_20210506-024801_sigmoid/hparams.txt b/models/model_20210506-024801_sigmoid/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.0404136]
+test_loss: [[0.00650297]
+ [0.0053346 ]
+ [0.00474136]
+ [0.00477508]
+ [0.00434636]
+ [0.00424521]
+ [0.00429393]
+ [0.00397451]
+ [0.04043235]
+ [0.0403258 ]
+ [0.04043892]
+ [0.04049728]
+ [0.04043292]
+ [0.04052813]
+ [0.04037973]
+ [0.04040314]
+ [0.0404946 ]
+ [0.04049032]
+ [0.04046083]
+ [0.0404136 ]]
+training time: h:0 m:7 s:2
diff --git a/models/model_20210506-024801_sigmoid/learning_curve.jpg b/models/model_20210506-024801_sigmoid/learning_curve.jpg
diff --git a/models/model_20210506-024801_sigmoid/model_20210506-024801.pt b/models/model_20210506-024801_sigmoid/model_20210506-024801.pt
diff --git a/models/model_20210506-024801_sigmoid/test_loss_20210506-024801.jpg b/models/model_20210506-024801_sigmoid/test_loss_20210506-024801.jpg
diff --git a/models/model_20210506-024801_sigmoid/test_loss_20210506-024801.npy b/models/model_20210506-024801_sigmoid/test_loss_20210506-024801.npy
diff --git a/models/model_20210506-024801_sigmoid/train_loss_20210506-024801.jpg b/models/model_20210506-024801_sigmoid/train_loss_20210506-024801.jpg
diff --git a/models/model_20210506-024801_sigmoid/train_loss_20210506-024801.npy b/models/model_20210506-024801_sigmoid/train_loss_20210506-024801.npy
diff --git a/models/model_20210506-050120/hparams.txt b/models/model_20210506-050120/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.00376571]
+test_loss: [[0.00873717]
+ [0.00700724]
+ [0.00624093]
+ [0.00582324]
+ [0.00537704]
+ [0.0051421 ]
+ [0.00510931]
+ [0.00479073]
+ [0.00481021]
+ [0.00461175]
+ [0.00460752]
+ [0.00441033]
+ [0.00426731]
+ [0.00414414]
+ [0.00410547]
+ [0.00397599]
+ [0.00416182]
+ [0.00390747]
+ [0.00391987]
+ [0.00376571]]
+training time: h:0 m:6 s:24
diff --git a/models/model_20210506-050120/learning_curve.jpg b/models/model_20210506-050120/learning_curve.jpg
diff --git a/models/model_20210506-050120/model_20210506-050120.pt b/models/model_20210506-050120/model_20210506-050120.pt
diff --git a/models/model_20210506-050120/test_loss_20210506-050120.jpg b/models/model_20210506-050120/test_loss_20210506-050120.jpg
diff --git a/models/model_20210506-050120/test_loss_20210506-050120.npy b/models/model_20210506-050120/test_loss_20210506-050120.npy
diff --git a/models/model_20210506-050120/train_loss_20210506-050120.jpg b/models/model_20210506-050120/train_loss_20210506-050120.jpg
diff --git a/models/model_20210506-050120/train_loss_20210506-050120.npy b/models/model_20210506-050120/train_loss_20210506-050120.npy
diff --git a/models/model_20210506-051200/hparams.txt b/models/model_20210506-051200/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.02439159]
+test_loss: [[0.03420103]
+ [0.0104777 ]
+ [0.00815089]
+ [0.00744235]
+ [0.04022742]
+ [0.03240201]
+ [0.03220778]
+ [0.02471894]
+ [0.0401059 ]
+ [0.016645  ]
+ [0.04021125]
+ [0.01480315]
+ [0.04021156]
+ [0.02495696]
+ [0.0243977 ]
+ [0.02427862]
+ [0.02544884]
+ [0.02419577]
+ [0.02415112]
+ [0.02439159]]
+training time: h:0 m:6 s:20
diff --git a/models/model_20210506-051200/learning_curve.jpg b/models/model_20210506-051200/learning_curve.jpg
diff --git a/models/model_20210506-051200/model_20210506-051200.pt b/models/model_20210506-051200/model_20210506-051200.pt
diff --git a/models/model_20210506-051200/test_loss_20210506-051200.jpg b/models/model_20210506-051200/test_loss_20210506-051200.jpg
diff --git a/models/model_20210506-051200/test_loss_20210506-051200.npy b/models/model_20210506-051200/test_loss_20210506-051200.npy
diff --git a/models/model_20210506-051200/train_loss_20210506-051200.jpg b/models/model_20210506-051200/train_loss_20210506-051200.jpg
diff --git a/models/model_20210506-051200/train_loss_20210506-051200.npy b/models/model_20210506-051200/train_loss_20210506-051200.npy
diff --git a/models/model_20210506-051826/hparams.txt b/models/model_20210506-051826/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.03064372]
+test_loss: [[0.03112303]
+ [0.03063456]
+ [0.03069884]
+ [0.03070091]
+ [0.03061627]
+ [0.03071266]
+ [0.0305542 ]
+ [0.03053091]
+ [0.03065423]
+ [0.03053825]
+ [0.0308224 ]
+ [0.03061396]
+ [0.03060174]
+ [0.0306754 ]
+ [0.03061336]
+ [0.03056623]
+ [0.0306121 ]
+ [0.03075451]
+ [0.03055138]
+ [0.03064372]]
+training time: h:0 m:6 s:19
diff --git a/models/model_20210506-051826/learning_curve.jpg b/models/model_20210506-051826/learning_curve.jpg
diff --git a/models/model_20210506-051826/model_20210506-051826.pt b/models/model_20210506-051826/model_20210506-051826.pt
diff --git a/models/model_20210506-051826/test_loss_20210506-051826.jpg b/models/model_20210506-051826/test_loss_20210506-051826.jpg
diff --git a/models/model_20210506-051826/test_loss_20210506-051826.npy b/models/model_20210506-051826/test_loss_20210506-051826.npy
diff --git a/models/model_20210506-051826/train_loss_20210506-051826.jpg b/models/model_20210506-051826/train_loss_20210506-051826.jpg
diff --git a/models/model_20210506-051826/train_loss_20210506-051826.npy b/models/model_20210506-051826/train_loss_20210506-051826.npy
diff --git a/models/model_20210506-052451/hparams.txt b/models/model_20210506-052451/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.02997749]
+test_loss: [[0.03164007]
+ [0.03017076]
+ [0.03005473]
+ [0.0300474 ]
+ [0.03000421]
+ [0.03003434]
+ [0.03004317]
+ [0.03003589]
+ [0.03015953]
+ [0.03005943]
+ [0.03008069]
+ [0.02997419]
+ [0.03001923]
+ [0.03005805]
+ [0.03004132]
+ [0.03004277]
+ [0.03012958]
+ [0.03010974]
+ [0.03015311]
+ [0.02997749]]
+training time: h:0 m:6 s:25
diff --git a/models/model_20210506-052451/learning_curve.jpg b/models/model_20210506-052451/learning_curve.jpg
diff --git a/models/model_20210506-052451/model_20210506-052451.pt b/models/model_20210506-052451/model_20210506-052451.pt
diff --git a/models/model_20210506-052451/test_loss_20210506-052451.jpg b/models/model_20210506-052451/test_loss_20210506-052451.jpg
diff --git a/models/model_20210506-052451/test_loss_20210506-052451.npy b/models/model_20210506-052451/test_loss_20210506-052451.npy
diff --git a/models/model_20210506-052451/train_loss_20210506-052451.jpg b/models/model_20210506-052451/train_loss_20210506-052451.jpg
diff --git a/models/model_20210506-052451/train_loss_20210506-052451.npy b/models/model_20210506-052451/train_loss_20210506-052451.npy
diff --git a/models/model_20210506-053123/hparams.txt b/models/model_20210506-053123/hparams.txt
@@ -0,0 +1,22 @@
+last test_loss: [0.03180446]
+test_loss: [[0.03527263]
+ [0.03267101]
+ [0.03195613]
+ [0.0317746 ]
+ [0.03181642]
+ [0.0318057 ]
+ [0.03175871]
+ [0.03171796]
+ [0.03176349]
+ [0.03180444]
+ [0.03173973]
+ [0.03176798]
+ [0.03174742]
+ [0.0317592 ]
+ [0.03175276]
+ [0.03180073]
+ [0.03171606]
+ [0.03195552]
+ [0.03178935]
+ [0.03180446]]
+training time: h:0 m:6 s:22
diff --git a/models/model_20210506-053123/learning_curve.jpg b/models/model_20210506-053123/learning_curve.jpg
diff --git a/models/model_20210506-053123/model_20210506-053123.pt b/models/model_20210506-053123/model_20210506-053123.pt
diff --git a/models/model_20210506-053123/test_loss_20210506-053123.jpg b/models/model_20210506-053123/test_loss_20210506-053123.jpg
diff --git a/models/model_20210506-053123/test_loss_20210506-053123.npy b/models/model_20210506-053123/test_loss_20210506-053123.npy
diff --git a/models/model_20210506-053123/train_loss_20210506-053123.jpg b/models/model_20210506-053123/train_loss_20210506-053123.jpg
diff --git a/models/model_20210506-053123/train_loss_20210506-053123.npy b/models/model_20210506-053123/train_loss_20210506-053123.npy
diff --git a/models/model_20210506-060128/hparams.txt b/models/model_20210506-060128/hparams.txt
@@ -0,0 +1,23 @@
+max_epochs: 15
+batch_size: 5
+learning_rate: 0.00184
+weight_decay: 0.00020957
+f1: 24
+k1: 3
+last test_loss: [0.04059655]
+test_loss: [[0.00800483]
+ [0.00658701]
+ [0.00608908]
+ [0.00532129]
+ [0.00491463]
+ [0.00481828]
+ [0.00657785]
+ [0.0059823 ]
+ [0.00486277]
+ [0.00470289]
+ [0.04054457]
+ [0.04050905]
+ [0.04055   ]
+ [0.04051444]
+ [0.04059655]]
+training time: h:0 m:4 s:44
diff --git a/models/model_20210506-060128/learning_curve.jpg b/models/model_20210506-060128/learning_curve.jpg
diff --git a/models/model_20210506-060128/model_20210506-060128.pt b/models/model_20210506-060128/model_20210506-060128.pt
diff --git a/models/model_20210506-060128/test_loss_20210506-060128.jpg b/models/model_20210506-060128/test_loss_20210506-060128.jpg
diff --git a/models/model_20210506-060128/test_loss_20210506-060128.npy b/models/model_20210506-060128/test_loss_20210506-060128.npy
diff --git a/models/model_20210506-060128/train_loss_20210506-060128.jpg b/models/model_20210506-060128/train_loss_20210506-060128.jpg
diff --git a/models/model_20210506-060128/train_loss_20210506-060128.npy b/models/model_20210506-060128/train_loss_20210506-060128.npy
diff --git a/models/model_20210506-061202/hparams.txt b/models/model_20210506-061202/hparams.txt
@@ -0,0 +1,23 @@
+max_epochs: 15
+batch_size: 5
+learning_rate: 0.000203228544324115
+weight_decay: 1.2697111322756407e-05
+f1: 24
+k1: 3
+last test_loss: [0.00490871]
+test_loss: [[0.00942542]
+ [0.00807117]
+ [0.00709147]
+ [0.00658547]
+ [0.00698589]
+ [0.00593312]
+ [0.00584494]
+ [0.00567217]
+ [0.00546132]
+ [0.00539046]
+ [0.00525101]
+ [0.00515217]
+ [0.00513384]
+ [0.00503964]
+ [0.00490871]]
+training time: h:0 m:4 s:59
diff --git a/models/model_20210506-061202/learning_curve.jpg b/models/model_20210506-061202/learning_curve.jpg
diff --git a/models/model_20210506-061202/model_20210506-061202.pt b/models/model_20210506-061202/model_20210506-061202.pt
diff --git a/models/model_20210506-061202/test_loss_20210506-061202.jpg b/models/model_20210506-061202/test_loss_20210506-061202.jpg
diff --git a/models/model_20210506-061202/test_loss_20210506-061202.npy b/models/model_20210506-061202/test_loss_20210506-061202.npy
diff --git a/models/model_20210506-061202/train_loss_20210506-061202.jpg b/models/model_20210506-061202/train_loss_20210506-061202.jpg
diff --git a/models/model_20210506-061202/train_loss_20210506-061202.npy b/models/model_20210506-061202/train_loss_20210506-061202.npy
diff --git a/models/model_20210506-062306/hparams.txt b/models/model_20210506-062306/hparams.txt
@@ -0,0 +1,23 @@
+max_epochs: 15
+batch_size: 5
+f1: 24
+k1: 3
+learning_rate: 0.000203228544324115
+weight_decay: 1.2697111322756407e-05
+last test_loss: [0.00422964]
+test_loss: [[0.00936869]
+ [0.00714576]
+ [0.00647498]
+ [0.00589099]
+ [0.00558233]
+ [0.00531443]
+ [0.00520697]
+ [0.00507637]
+ [0.0048417 ]
+ [0.0047039 ]
+ [0.00455466]
+ [0.00477791]
+ [0.00449089]
+ [0.00430649]
+ [0.00422964]]
+training time: h:0 m:5 s:30
diff --git a/models/model_20210506-062306/learning_curve.jpg b/models/model_20210506-062306/learning_curve.jpg
diff --git a/models/model_20210506-062306/model_20210506-062306.pt b/models/model_20210506-062306/model_20210506-062306.pt
diff --git a/models/model_20210506-062306/test_loss_20210506-062306.jpg b/models/model_20210506-062306/test_loss_20210506-062306.jpg
diff --git a/models/model_20210506-062306/test_loss_20210506-062306.npy b/models/model_20210506-062306/test_loss_20210506-062306.npy
diff --git a/models/model_20210506-062306/train_loss_20210506-062306.jpg b/models/model_20210506-062306/train_loss_20210506-062306.jpg
diff --git a/models/model_20210506-062306/train_loss_20210506-062306.npy b/models/model_20210506-062306/train_loss_20210506-062306.npy
diff --git a/models/model_20210506-062842/hparams.txt b/models/model_20210506-062842/hparams.txt
@@ -0,0 +1,23 @@
+max_epochs: 15
+batch_size: 5
+f1: 32
+k1: 3
+learning_rate: 0.000203228544324115
+weight_decay: 1.2697111322756407e-05
+last test_loss: [0.00387622]
+test_loss: [[0.00859414]
+ [0.00679519]
+ [0.00610648]
+ [0.00558913]
+ [0.00518311]
+ [0.00500454]
+ [0.00476132]
+ [0.00464809]
+ [0.00440924]
+ [0.0043967 ]
+ [0.00450505]
+ [0.00418117]
+ [0.00400594]
+ [0.00394423]
+ [0.00387622]]
+training time: h:0 m:6 s:1
diff --git a/models/model_20210506-062842/learning_curve.jpg b/models/model_20210506-062842/learning_curve.jpg
diff --git a/models/model_20210506-062842/model_20210506-062842.pt b/models/model_20210506-062842/model_20210506-062842.pt
diff --git a/models/model_20210506-062842/test_loss_20210506-062842.jpg b/models/model_20210506-062842/test_loss_20210506-062842.jpg
diff --git a/models/model_20210506-062842/test_loss_20210506-062842.npy b/models/model_20210506-062842/test_loss_20210506-062842.npy
diff --git a/models/model_20210506-062842/train_loss_20210506-062842.jpg b/models/model_20210506-062842/train_loss_20210506-062842.jpg
diff --git a/models/model_20210506-062842/train_loss_20210506-062842.npy b/models/model_20210506-062842/train_loss_20210506-062842.npy
diff --git a/models/model_20210506-063449/hparams.txt b/models/model_20210506-063449/hparams.txt
@@ -0,0 +1,6 @@
+max_epochs: 15
+batch_size: 5
+f1: 64
+k1: 3
+learning_rate: 0.000203228544324115
+weight_decay: 1.2697111322756407e-05