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@aloncohen1
Created January 29, 2023 21:46
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"execution_count": 11,
"metadata": {
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"source": [
"from sklearn.model_selection import train_test_split\n",
"train_texts, val_texts, train_tags, val_tags = train_test_split(tagtog_parser.iob_tags_df['text_list'].map(list).to_list(), \n",
" tagtog_parser.iob_tags_df['tags_list'].map(list).to_list(), \n",
" test_size=.2)"
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"# create tag2id & id2tag mapping dicts\n",
"unique_tags = set(tag for doc in tagtog_parser.iob_tags_df['tags_list'].map(list).to_list() for tag in doc)\n",
"tag2id = {tag: id for id, tag in enumerate(unique_tags)}\n",
"id2tag = {id: tag for tag, id in tag2id.items()}"
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"[('The', 'O'),\n",
" ('Bloc', 'O'),\n",
" ('Qubcois', 'O'),\n",
" ('will', 'O'),\n",
" ('launch', 'O'),\n",
" ('a', 'O'),\n",
" ('debate', 'O'),\n",
" ('on', 'O'),\n",
" ('the', 'O'),\n",
" ('support', 'O'),\n",
" ('mechanisms', 'O'),\n",
" ('that', 'O'),\n",
" ('could', 'O'),\n",
" ('be', 'O'),\n",
" ('provided', 'O'),\n",
" ('to', 'O'),\n",
" ('farmers', 'B-social_group'),\n",
" ('wishing', 'O'),\n",
" ('to', 'O'),\n",
" ('convert', 'O'),\n",
" ('to', 'O'),\n",
" ('organic', 'O'),\n",
" ('farming', 'O'),\n",
" ('.', 'O')]"
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