diff --git a/nbs/022_tslearner.ipynb b/nbs/022_tslearner.ipynb index f0520bd1..2061edb9 100644 --- a/nbs/022_tslearner.ipynb +++ b/nbs/022_tslearner.ipynb @@ -265,10 +265,10 @@ " \n", " \n", " 0\n", - " 1.464314\n", - " 0.233333\n", - " 1.400173\n", - " 0.166667\n", + " 1.446255\n", + " 0.266667\n", + " 1.403359\n", + " 0.300000\n", " 00:00\n", " \n", " \n", @@ -339,8 +339,8 @@ " \n", " \n", " 0\n", - " 1.438072\n", - " 0.200000\n", + " 1.286023\n", + " 0.400000\n", " 00:00\n", " \n", " \n", @@ -600,11 +600,11 @@ " \n", " \n", " 0\n", - " 221.817291\n", - " 14.270400\n", - " 209.151230\n", - " 14.046944\n", - " 00:01\n", + " 221.239578\n", + " 14.241582\n", + " 208.787231\n", + " 14.034328\n", + " 00:00\n", " \n", " \n", "" @@ -619,9 +619,9 @@ ], "source": [ "X, y, splits = get_regression_data('AppliancesEnergy', split_data=False)\n", - "X = X.astype('float32')\n", - "y = y.astype('float32')\n", "if X is not None: # This is to prevent a test fail when the data server is not available\n", + " X = X.astype('float32')\n", + " y = y.astype('float32')\n", " batch_tfms = [TSStandardize()]\n", " learn = TSRegressor(X, y, splits=splits, batch_tfms=batch_tfms, arch=None, metrics=mae, bs=512, train_metrics=True, device=default_device())\n", " learn.fit_one_cycle(1, 1e-4)" @@ -860,10 +860,10 @@ " \n", " \n", " 0\n", - " 4114.624023\n", - " 48.891418\n", - " 7991.095703\n", - " 74.791130\n", + " 4616.225098\n", + " 53.340523\n", + " 7969.317871\n", + " 74.670258\n", " 00:00\n", " \n", " \n", @@ -932,9 +932,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "/Users/nacho/notebooks/tsai/nbs/022_tslearner.ipynb saved at 2024-02-11 10:55:07\n", + "/Users/nacho/notebooks/tsai/nbs/022_tslearner.ipynb saved at 2024-02-11 13:56:13\n", "Correct notebook to script conversion! 😃\n", - "Sunday 11/02/24 10:55:10 CET\n" + "Sunday 11/02/24 13:56:16 CET\n" ] }, { diff --git a/nbs/models/test.pth b/nbs/models/test.pth index fcf8ad2e..7cd3f29a 100644 Binary files a/nbs/models/test.pth and b/nbs/models/test.pth differ