chore: minor lecun 1990 nb corrections

eschmidt42 · Feb 1, 2024 · d02d16f · d02d16f
1 parent 7ddd23a
commit d02d16f
Showing 1 changed file with 12 additions and 33 deletions.
diff --git a/nbs/convolution_lecun1990.ipynb b/nbs/convolution_lecun1990.ipynb
@@ -934,7 +934,8 @@
    "outputs": [],
    "source": [
     "ds = conv_lecun1990.DigitsDataset(X0, y0)\n",
-    "ds_test = conv_lecun1990.DigitsDataset(X1, y1)"
+    "ds_valid = conv_lecun1990.DigitsDataset(X1, y1)\n",
+    "ds_test = conv_lecun1990.DigitsDataset(X2, y2)"
    ]
   },
   {
@@ -945,6 +946,7 @@
    "source": [
     "batch_size = 1\n",
     "dataloader = DataLoader(ds, batch_size=batch_size, shuffle=False)\n",
+    "dataloader_valid = DataLoader(ds_valid, batch_size=500, shuffle=False)\n",
     "dataloader_test = DataLoader(ds_test, batch_size=500, shuffle=False)"
    ]
   },
@@ -1036,7 +1038,7 @@
     "    with torch.no_grad():\n",
     "        model.eval()\n",
     "        ys_pred, ys_true = [], []\n",
-    "        for xb, yb in dataloader_test:\n",
+    "        for xb, yb in dataloader_valid:\n",
     "            xb = xb.to(device)\n",
     "            yb = yb.to(device)\n",
     "            yb = conv_lecun1990.densify_y(yb)\n",
@@ -1354,13 +1356,13 @@
     ")\n",
     "dl_valid = DataLoader(\n",
     "    ds_valid,\n",
-    "    batch_size=20,\n",
+    "    batch_size=200,\n",
     "    collate_fn=rnnm_data.mnist_collate_train,\n",
     "    shuffle=False,\n",
     ")\n",
     "dl_test = DataLoader(\n",
     "    ds_test,\n",
-    "    batch_size=20,\n",
+    "    batch_size=200,\n",
     "    collate_fn=rnnm_data.mnist_collate_train,\n",
     "    shuffle=False,\n",
     ")"
@@ -1392,9 +1394,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "n_epochs = 20\n",
-    "lr = 0.2\n",
-    "optimizer = optim.SGD(model.parameters(), lr=lr)  # , momentum=1e-3\n",
+    "n_epochs = 10\n",
+    "lr = 1e-3\n",
+    "# optimizer = optim.SGD(model.parameters(), lr=lr)  # , momentum=1e-3\n",
+    "optimizer = optim.Adam(model.parameters(), lr=lr)\n",
     "# scheduler = optim.lr_scheduler.OneCycleLR(\n",
     "#     optimizer=optimizer,\n",
     "#     max_lr=lr,\n",
@@ -1444,15 +1447,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# TODO: add early stopping"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1524,21 +1518,6 @@
     "computing test set performance"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "ds_test = rnnm_data.MNISTDatasetTrain(X1, y1)\n",
-    "dl_test = DataLoader(\n",
-    "    ds_test,\n",
-    "    batch_size=500,\n",
-    "    collate_fn=rnnm_data.mnist_collate_train,\n",
-    "    shuffle=False,\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1584,8 +1563,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "* Accuracy: 92.65%\n",
-    "* Error rate: 7.35%"
+    "* Accuracy: 95.15%\n",
+    "* Error rate: 4.85%"
    ]
   },
   {