test

dvc.lock

@@ -52,13 +52,13 @@ stages:
           img_size: 256
           batch_size: 8
           fine_tune_args:
-            epochs: 8
+            epochs: 5
             base_lr: 0.01
     outs:
     - path: models/model.pkl
       hash: md5
-      md5: ae181ee054fdea0c2480eefcb76c2054
-      size: 200592
+      md5: ca6d9c823ce5a29f4eed6d94ca5a1353
+      size: 198608
   evaluate:
     cmd: python src/evaluate.py
     deps:
@@ -69,8 +69,8 @@ stages:
       nfiles: 24
     - path: models/model.pkl
       hash: md5
-      md5: ae181ee054fdea0c2480eefcb76c2054
-      size: 200592
+      md5: ca6d9c823ce5a29f4eed6d94ca5a1353
+      size: 198608
     - path: src/evaluate.py
       hash: md5
       md5: 3322a933cb37bcc6680aa145e8832e3c

params.yaml

@@ -2,17 +2,17 @@ base:
   random_seed: 42
 
 data_split:
-  test_regions: 
-    - REGION_1
+  test_regions:
+  - REGION_1
 
 train:
   valid_pct: 0.1
   arch: shufflenet_v2_x2_0
   img_size: 256
   batch_size: 8
   fine_tune_args:
-    epochs: 8
-    base_lr: 0.01
+    epochs: 5
+    base_lr: 0.01
 
 evaluate:
   n_samples_to_save: 10

results/evaluate/metrics.json

@@ -1,3 +1,3 @@
 {
-    "dice_multi": 0.8753494531469994
+    "dice_multi": 0.8550860843208705
 }

results/evaluate/plots/images.dvc

@@ -1,6 +1,6 @@
 outs:
-- md5: e34ca95270b31cf582c84d89935bd406.dir
-  size: 1260306
+- md5: 470cc36aaa6b9ba50e768682bed71b73.dir
+  size: 1260191
   nfiles: 10
   hash: md5
   path: images

results/train/metrics.json

@@ -1,10 +1,10 @@
 {
     "train": {
-        "loss": 0.02757701650261879
+        "loss": 0.03533046692609787
     },
     "eval": {
-        "loss": 0.02525826171040535
+        "loss": 0.023488717153668404
     },
-    "dice_multi": 0.890823607730554,
-    "step": 8
+    "dice_multi": 0.9013754762213613,
+    "step": 5
 }

results/train/plots/metrics/dice_multi.tsv

@@ -1,10 +1,7 @@
 step	dice_multi
-0	0.49586584320534516
-1	0.49586584320534516
-2	0.8447301191694103
-3	0.8642264229422093
-4	0.8745833361182084
-5	0.8882574957432371
-6	0.8794158684046307
-7	0.8903446664455691
-8	0.890823607730554
+0	0.49580101619694394
+1	0.4961951156354691
+2	0.8349846483268908
+3	0.8889560553781508
+4	0.8981627818104924
+5	0.9013754762213613

results/train/plots/metrics/eval/loss.tsv

@@ -1,10 +1,7 @@
 step	loss
-0	0.09114564210176468
-1	0.063581183552742
-2	0.03981240466237068
-3	0.03099050000309944
-4	0.029771974310278893
-5	0.025653092190623283
-6	0.029161425307393074
-7	0.025329558178782463
-8	0.02525826171040535
+0	0.08453821390867233
+1	0.05668149143457413
+2	0.039267394691705704
+3	0.02620350942015648
+4	0.023696910589933395
+5	0.023488717153668404

results/train/plots/metrics/train/loss.tsv

@@ -1,10 +1,7 @@
 step	loss
-0	0.323860764503479
-1	0.08164063841104507
-2	0.06180482730269432
-3	0.04931340366601944
-4	0.04120255261659622
-5	0.03628794103860855
-6	0.032480645924806595
-7	0.029709428548812866
-8	0.02757701650261879
+0	0.32418927550315857
+1	0.07955705374479294
+2	0.05694882571697235
+3	0.046153273433446884
+4	0.03968912735581398
+5	0.03533046692609787