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Sylvain Gugger 2020-03-21 08:38:44 -07:00
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18
01_intro.ipynb
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@ -2168,6 +2168,24 @@
"learn.fine_tune(4, 1e-2)" "learn.fine_tune(4, 1e-2)"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#clean\n",
"If you hit a \"CUDA out of memory error\" after running this cell, click on the menu Kernel, then restart. Instead of executing the cell above, copy and paste the following code in it:\n",
"\n",
"```\n",
"from fastai2.text.all import *\n",
"\n",
"dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test', bs=32)\n",
"learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)\n",
"learn.fine_tune(4, 1e-2)\n",
"```\n",
"\n",
"This reduces the batch size to 32 (we will explain this later). If you keep hitting the same error, change 32 by 16."
]
},
{ {
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},

17
clean/01_intro.ipynb
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@ -1072,6 +1072,23 @@
"learn.fine_tune(4, 1e-2)" "learn.fine_tune(4, 1e-2)"
] ]
}, },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you hit a \"CUDA out of memory error\" after running this cell, click on the menu Kernel, then restart. Instead of executing the cell above, copy and paste the following code in it:\n",
"\n",
"```\n",
"from fastai2.text.all import *\n",
"\n",
"dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test', bs=32)\n",
"learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)\n",
"learn.fine_tune(4, 1e-2)\n",
"```\n",
"\n",
"This reduces the batch size to 32 (we will explain this later). If you keep hitting the same error, change 32 by 16."
]
},
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,