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"output_type": "stream",
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"text": [
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"text": [
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"Requirement already satisfied: gensim in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (4.2.0)\n",
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"Requirement already satisfied: gensim in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (4.2.0)\n",
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"Requirement already satisfied: numpy>=1.17.0 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (1.22.3)\n",
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"Requirement already satisfied: smart-open>=1.8.1 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (6.0.0)\n",
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"Requirement already satisfied: scipy>=0.18.1 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (1.8.0)\n",
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"Requirement already satisfied: scipy>=0.18.1 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (1.8.0)\n",
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"Requirement already satisfied: smart-open>=1.8.1 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (6.0.0)\n"
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"Requirement already satisfied: numpy>=1.17.0 in /home/kuba/anaconda3/envs/zajeciaei/lib/python3.10/site-packages (from gensim) (1.22.3)\n"
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"name": "stderr",
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"/tmp/ipykernel_62420/1831104553.py:2: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
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"/tmp/ipykernel_5965/1831104553.py:2: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
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" from IPython.core.display import display, HTML\n"
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" from IPython.core.display import display, HTML\n"
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"Read 3M words\n",
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"Read 3M words\n",
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"Number of words: 275356\n",
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"Number of words: 275356\n",
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"Number of labels: 20\n",
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"Number of labels: 20\n",
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"Progress: 100.0% words/sec/thread: 1103389 lr: 0.000000 avg.loss: 0.817102 ETA: 0h 0m 0s\n"
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"Progress: 100.0% words/sec/thread: 1010736 lr: 0.000000 avg.loss: 0.817885 ETA: 0h 0m 0s\n"
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"name": "stdout",
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"text": [
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"0.7199946893255443\r\n"
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"0.719198088157196\r\n"
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}
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"!geval --metric Accuracy -o ss_20_newsgroup_test_pred_label_only -e 20_newsgroup_test_targets"
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"!geval --metric Accuracy -o ss_20_newsgroup_test_pred_label_only -e 20_newsgroup_test_targets"
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]
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]
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},
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Zadanie\n",
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"\n",
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"\n",
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"Ireland news na gonito. Proszę użyć gotowej biblioteki, innej niż w sklearn (np starspace, fasttext, vw). Reguły jak zawsze. Wynik powyżej 55 accuracy. "
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]
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": null,
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