Merge fixed-jiao-branch into exp-args

dvc.lock

@@ -33,23 +33,28 @@ stages:
           batch_size: 512
           latent_dim: 8
           duration: 00:00:30:00
-          max_epochs: 6
+          max_epochs: 2
           optim:
-            lr: 0.01
-        num_samples: 10000
+            lr: 0.009
+        num_samples: 100000
         seed: 423
     outs:
     - path: model
       hash: md5
-      md5: 7006e6dfdcbce27a2362214995586475.dir
-      size: 18561
+      md5: 8ca28cef25760bec7c9693de3a5ef94b.dir
+      size: 19905
+      nfiles: 1
+    - path: results/artifacts
+      hash: md5
+      md5: 8ca28cef25760bec7c9693de3a5ef94b.dir
+      size: 19905
       nfiles: 1
     - path: results/metrics.json
       hash: md5
-      md5: 098423a9c88c180638b8c06bc5457c53
-      size: 256
+      md5: a3bbb0726e96ecf43c4c5d81f4de112a
+      size: 367
     - path: results/plots
       hash: md5
-      md5: ec750cc202d7ea5723c50a8502249e73.dir
-      size: 149
-      nfiles: 5
+      md5: 6f4b1bb55939e1d359d1a5851dc9f50c.dir
+      size: 596
+      nfiles: 7

params.yaml

@@ -2,9 +2,9 @@ model:
   batch_size: 512
   latent_dim: 8
   duration: 00:00:30:00
-  max_epochs: 5
+  max_epochs: 2
   optim:
-    lr: 0.001
+    lr: 0.009
 data_path: fra.txt
-num_samples: 10000
+num_samples: 100000
 seed: 423

results/dvc.yaml

@@ -7,5 +7,5 @@ plots:
     x: step
 artifacts:
   best:
-    path: ../model/epoch=0-step=16.ckpt
+    path: artifacts/epoch=1-step=314.ckpt
     type: model

results/metrics.json

@@ -1,14 +1,18 @@
 {
-    "val": {
-        "loss": 0.871090829372406,
-        "acc": 0.012735245749354362
-    },
-    "epoch": 0,
-    "step": 15,
     "train": {
+        "step": {
+            "loss": 0.27118900418281555,
+            "acc": 0.06921477615833282
+        },
         "epoch": {
-            "loss": 1.7466247081756592,
-            "acc": 0.01202675886452198
+            "loss": 0.2750683128833771,
+            "acc": 0.05900849029421806
         }
+    },
+    "epoch": 1,
+    "step": 313,
+    "val": {
+        "loss": 0.26257047057151794,
+        "acc": 0.06994836777448654
     }
 }

results/params.yaml

@@ -1,3 +1,3 @@
-optim_params:
-  lr: 0.01
 latent_dim: 8
+optim_params:
+  lr: 0.009

results/plots/metrics/epoch.tsv

@@ -1,3 +1,11 @@
 step	epoch
-15	0
-15	0
+49	0
+99	0
+149	0
+156	0
+156	0
+199	1
+249	1
+299	1
+313	1
+313	1

results/plots/metrics/train/epoch/acc.tsv

@@ -1,2 +1,3 @@
 step	acc
-15	0.01202675886452198
+156	0.027291731908917427
+313	0.05900849029421806

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

@@ -1,2 +1,3 @@
 step	loss
-15	1.7466247081756592
+156	0.44763797521591187
+313	0.2750683128833771

results/plots/metrics/train/step/acc.tsv

@@ -0,0 +1,7 @@
+step	acc
+49	0.019934747368097305
+99	0.03165007382631302
+149	0.042517878115177155
+199	0.04552024230360985
+249	0.063819520175457
+299	0.06921477615833282

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

@@ -0,0 +1,7 @@
+step	loss
+49	0.35641106963157654
+99	0.3244558572769165
+149	0.2955430746078491
+199	0.2739129960536957
+249	0.2627813220024109
+299	0.27118900418281555

results/plots/metrics/val/acc.tsv

@@ -0,0 +1,3 @@
+step	acc
+156	0.041722372174263
+313	0.06994836777448654

results/plots/metrics/val/loss.tsv

@@ -0,0 +1,3 @@
+step	loss
+156	0.29371124505996704
+313	0.26257047057151794