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"!pip install -q -U transformers[sentencepiece] rouge git+https://github.com/deepset-ai/haystack.git grpcio-tools==1.34.1 spacy" |
|
|
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], |
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"execution_count": 11, |
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|
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"outputs": [] |
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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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"metadata": { |
|
|
380 |
"id": "1EHR4i9FiCAa" |
|
|
381 |
}, |
|
|
382 |
"source": [ |
|
|
383 |
"import spacy\n", |
|
|
384 |
"import nltk\n", |
|
|
385 |
"import json\n", |
|
|
386 |
"from tqdm import tqdm\n", |
|
|
387 |
"import pandas as pd \n", |
|
|
388 |
"from rouge import Rouge\n", |
|
|
389 |
"from pprint import pprint\n", |
|
|
390 |
"from typing import List\n", |
|
|
391 |
"from haystack import Document\n", |
|
|
392 |
"from haystack.reader import TransformersReader\n", |
|
|
393 |
"from haystack.pipeline import ExtractiveQAPipeline \n", |
|
|
394 |
"from haystack.retriever.dense import DensePassageRetriever \n", |
|
|
395 |
"from haystack.document_store.faiss import FAISSDocumentStore\n", |
|
|
396 |
"from nltk.translate.bleu_score import sentence_bleu, SmoothingFunction" |
|
|
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], |
|
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"execution_count": 12, |
|
|
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"outputs": [] |
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}, |
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{ |
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"cell_type": "code", |
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"metadata": { |
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|
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"colab": { |
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"base_uri": "https://localhost:8080/" |
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}, |
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"id": "gyHgtCYAXEZb", |
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"outputId": "824bdab5-4c5b-4064-8efd-b0bfc2798827" |
|
|
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}, |
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"source": [ |
|
|
411 |
"!spacy download en_core_web_md \n", |
|
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"!spacy link en_core_web_md en" |
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], |
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"execution_count": 13, |
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"outputs": [ |
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{ |
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"output_type": "stream", |
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"name": "stdout", |
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"text": [ |
|
|
420 |
"Collecting en-core-web-md==3.1.0\n", |
|
|
421 |
" Downloading https://github.com/explosion/spacy-models/releases/download/en_core_web_md-3.1.0/en_core_web_md-3.1.0-py3-none-any.whl (45.4 MB)\n", |
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"\u001b[K |████████████████████████████████| 45.4 MB 17 kB/s \n", |
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"\u001b[?25hRequirement already satisfied: spacy<3.2.0,>=3.1.0 in /usr/local/lib/python3.7/dist-packages (from en-core-web-md==3.1.0) (3.1.3)\n", |
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424 |
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (21.0)\n", |
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"Requirement already satisfied: typer<0.5.0,>=0.3.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (0.4.0)\n", |
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"Requirement already satisfied: pydantic!=1.8,!=1.8.1,<1.9.0,>=1.7.4 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (1.8.2)\n", |
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"Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.0.5)\n", |
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"Requirement already satisfied: blis<0.8.0,>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (0.4.1)\n", |
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"Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (1.19.5)\n", |
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"Requirement already satisfied: pathy>=0.3.5 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (0.6.0)\n", |
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"Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (4.62.2)\n", |
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"Requirement already satisfied: thinc<8.1.0,>=8.0.9 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (8.0.10)\n", |
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"Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.8 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (3.0.8)\n", |
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"Requirement already satisfied: jinja2 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.11.3)\n", |
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"Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (3.0.5)\n", |
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"Requirement already satisfied: srsly<3.0.0,>=2.4.1 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.4.1)\n", |
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"Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (57.4.0)\n", |
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439 |
"Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.0.6)\n", |
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"Requirement already satisfied: typing-extensions<4.0.0.0,>=3.7.4 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (3.7.4.3)\n", |
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"Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.23.0)\n", |
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"Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.7/dist-packages (from spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (1.0.5)\n", |
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443 |
"Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from catalogue<2.1.0,>=2.0.6->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (3.5.0)\n", |
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"Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.4.7)\n", |
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445 |
"Requirement already satisfied: smart-open<6.0.0,>=5.0.0 in /usr/local/lib/python3.7/dist-packages (from pathy>=0.3.5->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (5.2.1)\n", |
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"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (1.25.11)\n", |
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"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2021.5.30)\n", |
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448 |
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.10)\n", |
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449 |
"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (3.0.4)\n", |
|
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450 |
"Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.7/dist-packages (from typer<0.5.0,>=0.3.0->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (7.1.2)\n", |
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451 |
"Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.7/dist-packages (from jinja2->spacy<3.2.0,>=3.1.0->en-core-web-md==3.1.0) (2.0.1)\n", |
|
|
452 |
"\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n", |
|
|
453 |
"You can now load the package via spacy.load('en_core_web_md')\n", |
|
|
454 |
"\u001b[31mDeprecationWarning: The command link is deprecated.\u001b[0m\n", |
|
|
455 |
"\u001b[38;5;3m⚠ As of spaCy v3.0, model symlinks are not supported anymore. You can\n", |
|
|
456 |
"load trained pipeline packages using their full names or from a directory\n", |
|
|
457 |
"path.\u001b[0m\n" |
|
|
458 |
] |
|
|
459 |
} |
|
|
460 |
] |
|
|
461 |
}, |
|
|
462 |
{ |
|
|
463 |
"cell_type": "code", |
|
|
464 |
"metadata": { |
|
|
465 |
"colab": { |
|
|
466 |
"base_uri": "https://localhost:8080/" |
|
|
467 |
}, |
|
|
468 |
"id": "K7ipay4bguxX", |
|
|
469 |
"outputId": "a54705c6-fea4-4533-a4c9-638e46d49c89" |
|
|
470 |
}, |
|
|
471 |
"source": [ |
|
|
472 |
"nltk.download('punkt')" |
|
|
473 |
], |
|
|
474 |
"execution_count": 22, |
|
|
475 |
"outputs": [ |
|
|
476 |
{ |
|
|
477 |
"output_type": "stream", |
|
|
478 |
"name": "stdout", |
|
|
479 |
"text": [ |
|
|
480 |
"[nltk_data] Downloading package punkt to /root/nltk_data...\n", |
|
|
481 |
"[nltk_data] Unzipping tokenizers/punkt.zip.\n" |
|
|
482 |
] |
|
|
483 |
}, |
|
|
484 |
{ |
|
|
485 |
"output_type": "execute_result", |
|
|
486 |
"data": { |
|
|
487 |
"text/plain": [ |
|
|
488 |
"True" |
|
|
489 |
] |
|
|
490 |
}, |
|
|
491 |
"metadata": {}, |
|
|
492 |
"execution_count": 22 |
|
|
493 |
} |
|
|
494 |
] |
|
|
495 |
}, |
|
|
496 |
{ |
|
|
497 |
"cell_type": "code", |
|
|
498 |
"metadata": { |
|
|
499 |
"colab": { |
|
|
500 |
"base_uri": "https://localhost:8080/" |
|
|
501 |
}, |
|
|
502 |
"id": "fhLYC0ivc0A_", |
|
|
503 |
"outputId": "a48b2a6c-f1f9-4ab3-e14f-f777c295901c" |
|
|
504 |
}, |
|
|
505 |
"source": [ |
|
|
506 |
"import spacy\n", |
|
|
507 |
"# nlp = spacy.load('en_core_web_md')\n", |
|
|
508 |
"nlp = English() \n", |
|
|
509 |
"nlp.add_pipe(\"sentencizer\")" |
|
|
510 |
], |
|
|
511 |
"execution_count": 61, |
|
|
512 |
"outputs": [ |
|
|
513 |
{ |
|
|
514 |
"output_type": "execute_result", |
|
|
515 |
"data": { |
|
|
516 |
"text/plain": [ |
|
|
517 |
"<spacy.pipeline.sentencizer.Sentencizer at 0x7f4ea4ea7640>" |
|
|
518 |
] |
|
|
519 |
}, |
|
|
520 |
"metadata": {}, |
|
|
521 |
"execution_count": 61 |
|
|
522 |
} |
|
|
523 |
] |
|
|
524 |
}, |
|
|
525 |
{ |
|
|
526 |
"cell_type": "code", |
|
|
527 |
"metadata": { |
|
|
528 |
"colab": { |
|
|
529 |
"base_uri": "https://localhost:8080/" |
|
|
530 |
}, |
|
|
531 |
"id": "ZkXrmWA1ViH-", |
|
|
532 |
"outputId": "bf834313-8fff-49bf-9cce-cab06f0f7d1d" |
|
|
533 |
}, |
|
|
534 |
"source": [ |
|
|
535 |
"from google.colab import drive\n", |
|
|
536 |
"drive.mount('/content/drive')" |
|
|
537 |
], |
|
|
538 |
"execution_count": 15, |
|
|
539 |
"outputs": [ |
|
|
540 |
{ |
|
|
541 |
"output_type": "stream", |
|
|
542 |
"name": "stdout", |
|
|
543 |
"text": [ |
|
|
544 |
"Mounted at /content/drive\n" |
|
|
545 |
] |
|
|
546 |
} |
|
|
547 |
] |
|
|
548 |
}, |
|
|
549 |
{ |
|
|
550 |
"cell_type": "code", |
|
|
551 |
"metadata": { |
|
|
552 |
"id": "S8XOUzQpwLw9" |
|
|
553 |
}, |
|
|
554 |
"source": [ |
|
|
555 |
"with open('drive/MyDrive/qa_test.json', \"r\") as f:\n", |
|
|
556 |
" qa = json.loads(f.read())['data']\n", |
|
|
557 |
"\n", |
|
|
558 |
"df = pd.read_csv('drive/MyDrive/ex-QA.csv', index_col=0)\n", |
|
|
559 |
"df = df.replace(r'\\n',' ', regex=True) " |
|
|
560 |
], |
|
|
561 |
"execution_count": 16, |
|
|
562 |
"outputs": [] |
|
|
563 |
}, |
|
|
564 |
{ |
|
|
565 |
"cell_type": "code", |
|
|
566 |
"metadata": { |
|
|
567 |
"id": "fbsJedAQ1mBF" |
|
|
568 |
}, |
|
|
569 |
"source": [ |
|
|
570 |
"titles = list(df[\"title\"].values)\n", |
|
|
571 |
"texts = list(df[\"text\"].values)\n", |
|
|
572 |
"documents: List[Document] = []\n", |
|
|
573 |
" \n", |
|
|
574 |
"for title, text in zip(titles, texts):\n", |
|
|
575 |
" documents.append(\n", |
|
|
576 |
" Document(\n", |
|
|
577 |
" text=text,\n", |
|
|
578 |
" meta={\n", |
|
|
579 |
" \"name\": title or \"\"\n", |
|
|
580 |
" }\n", |
|
|
581 |
" )\n", |
|
|
582 |
" )" |
|
|
583 |
], |
|
|
584 |
"execution_count": 17, |
|
|
585 |
"outputs": [] |
|
|
586 |
}, |
|
|
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{ |
|
|
588 |
"cell_type": "code", |
|
|
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"metadata": { |
|
|
590 |
"colab": { |
|
|
591 |
"base_uri": "https://localhost:8080/", |
|
|
592 |
"height": 108, |
|
|
593 |
"referenced_widgets": [ |
|
|
594 |
"adb6799fa25e4bc7adf1212f63f04973", |
|
|
595 |
"d79b5216eea84819adca4b226b63cdf2", |
|
|
596 |
"a31c486541af49d29a33720649112c4d", |
|
|
597 |
"daf91846ad164d55a741bf9c7894d7de", |
|
|
598 |
"6614bcfbf2e64961b8d4a36a8fa0942f", |
|
|
599 |
"5295e24c499249ee814331ddd6d0f984", |
|
|
600 |
"8eb53342f51c4307b5c2f98de2baf3e0", |
|
|
601 |
"1e85d3a19e6941c08a43fb531cf407dc", |
|
|
602 |
"982358c88a9a44b48ae915b4e3b9b46b", |
|
|
603 |
"1c518d3f76424c609b6f085ae15de0c8", |
|
|
604 |
"b2aaec2787ff4e17bddb01515d5d7068" |
|
|
605 |
] |
|
|
606 |
}, |
|
|
607 |
"id": "pDemzc4-kPww", |
|
|
608 |
"outputId": "85a2e13c-4c01-4238-ce7b-576247e989a6" |
|
|
609 |
}, |
|
|
610 |
"source": [ |
|
|
611 |
"document_store = FAISSDocumentStore(\n", |
|
|
612 |
" faiss_index_factory_str=\"Flat\",\n", |
|
|
613 |
" return_embedding=True\n", |
|
|
614 |
")\n", |
|
|
615 |
"\n", |
|
|
616 |
"retriever = DensePassageRetriever(\n", |
|
|
617 |
" document_store=document_store,\n", |
|
|
618 |
" query_embedding_model=\"facebook/dpr-question_encoder-single-nq-base\",\n", |
|
|
619 |
" passage_embedding_model=\"facebook/dpr-ctx_encoder-single-nq-base\",\n", |
|
|
620 |
" use_gpu=True,\n", |
|
|
621 |
" embed_title=True,\n", |
|
|
622 |
")\n", |
|
|
623 |
"\n", |
|
|
624 |
"# retriever = DensePassageRetriever(\n", |
|
|
625 |
"# document_store=document_store,\n", |
|
|
626 |
"# query_embedding_model=\"drive/MyDrive/bert-large-finetuned\",\n", |
|
|
627 |
"# passage_embedding_model=\"drive/MyDrive/bert-large-finetuned\",\n", |
|
|
628 |
"# use_gpu=True,\n", |
|
|
629 |
"# embed_title=True,\n", |
|
|
630 |
"# )\n", |
|
|
631 |
"\n", |
|
|
632 |
"document_store.delete_documents()\n", |
|
|
633 |
"document_store.write_documents(documents)\n", |
|
|
634 |
"document_store.update_embeddings(\n", |
|
|
635 |
" retriever=retriever\n", |
|
|
636 |
")" |
|
|
637 |
], |
|
|
638 |
"execution_count": 85, |
|
|
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"outputs": [ |
|
|
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{ |
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|
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"output_type": "stream", |
|
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"name": "stderr", |
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"text": [ |
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|
644 |
"09/24/2021 21:45:40 - WARNING - farm.utils - Failed to log params: Changing param values is not allowed. Param with key='lm1_name' was already logged with value='drive/MyDrive/squeeze-bert-finetuned' for run ID='57f858c4db2047c3a6013ad6593d2c9b'. Attempted logging new value 'facebook/dpr-question_encoder-single-nq-base'.\n", |
|
|
645 |
"09/24/2021 21:46:02 - INFO - haystack.document_store.faiss - Updating embeddings for 7330 docs...\n", |
|
|
646 |
"Updating Embedding: 0%| | 0/7330 [00:00<?, ? docs/s]" |
|
|
647 |
] |
|
|
648 |
}, |
|
|
649 |
{ |
|
|
650 |
"output_type": "display_data", |
|
|
651 |
"data": { |
|
|
652 |
"application/vnd.jupyter.widget-view+json": { |
|
|
653 |
"model_id": "adb6799fa25e4bc7adf1212f63f04973", |
|
|
654 |
"version_minor": 0, |
|
|
655 |
"version_major": 2 |
|
|
656 |
}, |
|
|
657 |
"text/plain": [ |
|
|
658 |
"Create embeddings: 0%| | 0/7344 [00:00<?, ? Docs/s]" |
|
|
659 |
] |
|
|
660 |
}, |
|
|
661 |
"metadata": {} |
|
|
662 |
}, |
|
|
663 |
{ |
|
|
664 |
"output_type": "stream", |
|
|
665 |
"name": "stderr", |
|
|
666 |
"text": [ |
|
|
667 |
"Documents Processed: 10000 docs [03:58, 41.92 docs/s]\n" |
|
|
668 |
] |
|
|
669 |
} |
|
|
670 |
] |
|
|
671 |
}, |
|
|
672 |
{ |
|
|
673 |
"cell_type": "code", |
|
|
674 |
"metadata": { |
|
|
675 |
"id": "TifruTY50Lsn" |
|
|
676 |
}, |
|
|
677 |
"source": [ |
|
|
678 |
"# reader = TransformersReader(model_name_or_path=\"ahotrod/albert_xxlargev1_squad2_512\", use_gpu=0)\n", |
|
|
679 |
"# reader = TransformersReader(model_name_or_path=\"bert-large-uncased-whole-word-masking-finetuned-squad\", use_gpu=0)\n", |
|
|
680 |
"\n", |
|
|
681 |
"reader = TransformersReader(model_name_or_path=\"ktrapeznikov/albert-xlarge-v2-squad-v2\", \n", |
|
|
682 |
" context_window_size=70,\n", |
|
|
683 |
" max_seq_len=256,\n", |
|
|
684 |
" doc_stride=128,\n", |
|
|
685 |
" use_gpu=0)\n", |
|
|
686 |
"\n", |
|
|
687 |
"# reader = TransformersReader(model_name_or_path=\"drive/MyDrive/bert_basefi_qafi\", \n", |
|
|
688 |
"# context_window_size=70,\n", |
|
|
689 |
"# max_seq_len=256,\n", |
|
|
690 |
"# doc_stride=128,\n", |
|
|
691 |
"# use_gpu=0)\n", |
|
|
692 |
"\n", |
|
|
693 |
"pipe = ExtractiveQAPipeline(reader, retriever)" |
|
|
694 |
], |
|
|
695 |
"execution_count": 165, |
|
|
696 |
"outputs": [] |
|
|
697 |
}, |
|
|
698 |
{ |
|
|
699 |
"cell_type": "markdown", |
|
|
700 |
"metadata": { |
|
|
701 |
"id": "aPhP2TZdA_5l" |
|
|
702 |
}, |
|
|
703 |
"source": [ |
|
|
704 |
"# Answers Bleu and Rouge" |
|
|
705 |
] |
|
|
706 |
}, |
|
|
707 |
{ |
|
|
708 |
"cell_type": "code", |
|
|
709 |
"metadata": { |
|
|
710 |
"id": "nuH1yj2f5rer", |
|
|
711 |
"colab": { |
|
|
712 |
"base_uri": "https://localhost:8080/" |
|
|
713 |
}, |
|
|
714 |
"outputId": "88e86ed4-15f2-4f6e-af14-1ffed31c3500" |
|
|
715 |
}, |
|
|
716 |
"source": [ |
|
|
717 |
"bleu_scores = []\n", |
|
|
718 |
"rouge1_scores = []\n", |
|
|
719 |
"rouge2_scores = []\n", |
|
|
720 |
"rougel_scores = []\n", |
|
|
721 |
"context_detection = []\n", |
|
|
722 |
"\n", |
|
|
723 |
"rouge = Rouge()\n", |
|
|
724 |
"smoothie = SmoothingFunction().method4\n", |
|
|
725 |
"\n", |
|
|
726 |
"for data in tqdm(qa):\n", |
|
|
727 |
" true_context = data['context']\n", |
|
|
728 |
" true_context = true_context.replace('\\n', ' ')\n", |
|
|
729 |
"\n", |
|
|
730 |
" for q_a in data['qas']:\n", |
|
|
731 |
" question = q_a['question']\n", |
|
|
732 |
" reference = \" \".join(q_a['answers'])\n", |
|
|
733 |
" preds = pipe.run(\n", |
|
|
734 |
" query=question,\n", |
|
|
735 |
" params={\"Retriever\": {\"top_k\": 3}, \"Reader\": {\"top_k\": 2}}\n", |
|
|
736 |
" )\n", |
|
|
737 |
" \n", |
|
|
738 |
" candidate_sent_list = []\n", |
|
|
739 |
" pred_context_list = [pred.to_dict()['text'] for pred in preds['documents']]\n", |
|
|
740 |
" pred_context = ' '.join(pred_context_list)\n", |
|
|
741 |
" pred_context = pred_context.replace('\\n', ' ')\n", |
|
|
742 |
" doc = nlp(pred_context)\n", |
|
|
743 |
" pred_context_sents = list(doc.sents)\n", |
|
|
744 |
"\n", |
|
|
745 |
" for pred_co in pred_context_list:\n", |
|
|
746 |
" pred_co = \"\".join(pred_co.rstrip().lstrip())\n", |
|
|
747 |
" if pred_co in true_context:\n", |
|
|
748 |
" context_detection.append(1)\n", |
|
|
749 |
" else:\n", |
|
|
750 |
" context_detection.append(0)\n", |
|
|
751 |
"\n", |
|
|
752 |
" for pred in preds['answers']:\n", |
|
|
753 |
" pred_answer = pred['answer']\n", |
|
|
754 |
"\n", |
|
|
755 |
" if pred_answer is not None:\n", |
|
|
756 |
" pred_answer = pred_answer.replace('\\n', ' ')\n", |
|
|
757 |
" doc = nlp(pred_answer)\n", |
|
|
758 |
" pred_answer_sents = list(doc.sents)\n", |
|
|
759 |
"\n", |
|
|
760 |
" for pred_context_sent in pred_context_sents:\n", |
|
|
761 |
" for pred_answer_sent in pred_answer_sents:\n", |
|
|
762 |
" pred_answer_sent = \"\".join(pred_answer_sent.text.rstrip().lstrip())\n", |
|
|
763 |
"\n", |
|
|
764 |
" if pred_answer_sent in pred_context_sent.text:\n", |
|
|
765 |
" candidate_sent_list.append(pred_context_sent.text)\n", |
|
|
766 |
"\n", |
|
|
767 |
"\n", |
|
|
768 |
" candidate_sent_set = set(candidate_sent_list)\n", |
|
|
769 |
" candidate = \" \".join(candidate_sent_set)\n", |
|
|
770 |
" token_reference = nltk.word_tokenize(reference)\n", |
|
|
771 |
" token_candidate = nltk.word_tokenize(candidate)\n", |
|
|
772 |
"\n", |
|
|
773 |
" bleu_score = sentence_bleu(token_reference, \n", |
|
|
774 |
" token_candidate, \n", |
|
|
775 |
" smoothing_function=smoothie, \n", |
|
|
776 |
" weights=(1, 0, 0, 0))\n", |
|
|
777 |
" rouge_score = rouge.get_scores(candidate, reference)\n", |
|
|
778 |
"\n", |
|
|
779 |
" bleu_scores.append(bleu_score)\n", |
|
|
780 |
" rouge1_scores.append(rouge_score[0]['rouge-1']['f'])\n", |
|
|
781 |
" rouge2_scores.append(rouge_score[0]['rouge-2']['f'])\n", |
|
|
782 |
" rougel_scores.append(rouge_score[0]['rouge-l']['f'])" |
|
|
783 |
], |
|
|
784 |
"execution_count": 166, |
|
|
785 |
"outputs": [ |
|
|
786 |
{ |
|
|
787 |
"output_type": "stream", |
|
|
788 |
"name": "stderr", |
|
|
789 |
"text": [ |
|
|
790 |
"100%|██████████| 38/38 [10:04<00:00, 15.90s/it]\n" |
|
|
791 |
] |
|
|
792 |
} |
|
|
793 |
] |
|
|
794 |
}, |
|
|
795 |
{ |
|
|
796 |
"cell_type": "code", |
|
|
797 |
"metadata": { |
|
|
798 |
"colab": { |
|
|
799 |
"base_uri": "https://localhost:8080/" |
|
|
800 |
}, |
|
|
801 |
"id": "fbNvejJDz_Pf", |
|
|
802 |
"outputId": "a94abda7-6172-4bd8-efcf-806f12647fda" |
|
|
803 |
}, |
|
|
804 |
"source": [ |
|
|
805 |
"context_detection.count(1) / len(context_detection)" |
|
|
806 |
], |
|
|
807 |
"execution_count": 167, |
|
|
808 |
"outputs": [ |
|
|
809 |
{ |
|
|
810 |
"output_type": "execute_result", |
|
|
811 |
"data": { |
|
|
812 |
"text/plain": [ |
|
|
813 |
"0.046413502109704644" |
|
|
814 |
] |
|
|
815 |
}, |
|
|
816 |
"metadata": {}, |
|
|
817 |
"execution_count": 167 |
|
|
818 |
} |
|
|
819 |
] |
|
|
820 |
}, |
|
|
821 |
{ |
|
|
822 |
"cell_type": "code", |
|
|
823 |
"metadata": { |
|
|
824 |
"id": "TJoBQVepyXVo", |
|
|
825 |
"colab": { |
|
|
826 |
"base_uri": "https://localhost:8080/" |
|
|
827 |
}, |
|
|
828 |
"outputId": "91927d4e-aad4-4f83-c0f8-393b213d0274" |
|
|
829 |
}, |
|
|
830 |
"source": [ |
|
|
831 |
"print(\"bleu -->\", sum(bleu_scores)/len(bleu_scores))\n", |
|
|
832 |
"print(\"rouge1 -->\", sum(rouge1_scores)/len(rouge1_scores))\n", |
|
|
833 |
"print(\"rouge2 -->\", sum(rouge2_scores)/len(rouge2_scores))\n", |
|
|
834 |
"print(\"rougel -->\", sum(rougel_scores)/len(rougel_scores))" |
|
|
835 |
], |
|
|
836 |
"execution_count": 168, |
|
|
837 |
"outputs": [ |
|
|
838 |
{ |
|
|
839 |
"output_type": "stream", |
|
|
840 |
"name": "stdout", |
|
|
841 |
"text": [ |
|
|
842 |
"bleu --> 0.0700302475143219\n", |
|
|
843 |
"rouge1 --> 0.2025044353996794\n", |
|
|
844 |
"rouge2 --> 0.11069682602623314\n", |
|
|
845 |
"rougel --> 0.1903201590307057\n" |
|
|
846 |
] |
|
|
847 |
} |
|
|
848 |
] |
|
|
849 |
}, |
|
|
850 |
{ |
|
|
851 |
"cell_type": "markdown", |
|
|
852 |
"metadata": { |
|
|
853 |
"id": "aa7Wjif33yoC" |
|
|
854 |
}, |
|
|
855 |
"source": [ |
|
|
856 |
"# facebook/dpr-question_encoder-single-nq-base + Fine Tuned Bert on (Squad + Our Dataset)" |
|
|
857 |
] |
|
|
858 |
}, |
|
|
859 |
{ |
|
|
860 |
"cell_type": "markdown", |
|
|
861 |
"metadata": { |
|
|
862 |
"id": "SJqLRURR5Nwu" |
|
|
863 |
}, |
|
|
864 |
"source": [ |
|
|
865 |
"# 3, 2\n", |
|
|
866 |
"\n", |
|
|
867 |
"```\n", |
|
|
868 |
"bleu --> 0.06931287859597637\n", |
|
|
869 |
"rouge1 --> 0.19821744629020724\n", |
|
|
870 |
"rouge2 --> 0.10658866102635696\n", |
|
|
871 |
"rougel --> 0.1868117643779736\n", |
|
|
872 |
"```" |
|
|
873 |
] |
|
|
874 |
}, |
|
|
875 |
{ |
|
|
876 |
"cell_type": "markdown", |
|
|
877 |
"metadata": { |
|
|
878 |
"id": "-3mFCty4EXQ6" |
|
|
879 |
}, |
|
|
880 |
"source": [ |
|
|
881 |
"# 3, 5\n", |
|
|
882 |
"\n", |
|
|
883 |
"```\n", |
|
|
884 |
"bleu --> 0.03326668172125407\n", |
|
|
885 |
"rouge1 --> 0.20946994043485553\n", |
|
|
886 |
"rouge2 --> 0.10167689243447016\n", |
|
|
887 |
"rougel --> 0.19906621627604376\n", |
|
|
888 |
"```" |
|
|
889 |
] |
|
|
890 |
}, |
|
|
891 |
{ |
|
|
892 |
"cell_type": "markdown", |
|
|
893 |
"metadata": { |
|
|
894 |
"id": "isTlazUFE1V8" |
|
|
895 |
}, |
|
|
896 |
"source": [ |
|
|
897 |
"# 3, 7\n", |
|
|
898 |
"\n", |
|
|
899 |
"```\n", |
|
|
900 |
"bleu --> 0.02560506763859031\n", |
|
|
901 |
"rouge1 --> 0.19673322385299405\n", |
|
|
902 |
"rouge2 --> 0.08888356388695941\n", |
|
|
903 |
"rougel --> 0.18626961745270976\n", |
|
|
904 |
"```" |
|
|
905 |
] |
|
|
906 |
}, |
|
|
907 |
{ |
|
|
908 |
"cell_type": "markdown", |
|
|
909 |
"metadata": { |
|
|
910 |
"id": "g1wJpZ8r4GlW" |
|
|
911 |
}, |
|
|
912 |
"source": [ |
|
|
913 |
"# 5, 2\n", |
|
|
914 |
"\n", |
|
|
915 |
"```\n", |
|
|
916 |
"bleu --> 0.06345328647077997\n", |
|
|
917 |
"rouge1 --> 0.20406716478695625\n", |
|
|
918 |
"rouge2 --> 0.1060285107744637\n", |
|
|
919 |
"rougel --> 0.19283290551462437\n", |
|
|
920 |
"```" |
|
|
921 |
] |
|
|
922 |
}, |
|
|
923 |
{ |
|
|
924 |
"cell_type": "markdown", |
|
|
925 |
"metadata": { |
|
|
926 |
"id": "vz93n0QzGKeF" |
|
|
927 |
}, |
|
|
928 |
"source": [ |
|
|
929 |
"# 5, 3\n", |
|
|
930 |
"\n", |
|
|
931 |
"```\n", |
|
|
932 |
"bleu --> 0.04911886384092217\n", |
|
|
933 |
"rouge1 --> 0.21052577428485436\n", |
|
|
934 |
"rouge2 --> 0.10274851606324212\n", |
|
|
935 |
"rougel --> 0.19822657706745186\n", |
|
|
936 |
"```" |
|
|
937 |
] |
|
|
938 |
}, |
|
|
939 |
{ |
|
|
940 |
"cell_type": "markdown", |
|
|
941 |
"metadata": { |
|
|
942 |
"id": "bQlxsR8cFfDL" |
|
|
943 |
}, |
|
|
944 |
"source": [ |
|
|
945 |
"# 5, 5\n", |
|
|
946 |
"\n", |
|
|
947 |
"```\n", |
|
|
948 |
"bleu --> 0.03170644661963682\n", |
|
|
949 |
"rouge1 --> 0.21191987555043731\n", |
|
|
950 |
"rouge2 --> 0.1037352111344695\n", |
|
|
951 |
"rougel --> 0.20209905658726562\n", |
|
|
952 |
"```" |
|
|
953 |
] |
|
|
954 |
}, |
|
|
955 |
{ |
|
|
956 |
"cell_type": "markdown", |
|
|
957 |
"metadata": { |
|
|
958 |
"id": "LYliZ6kU4_IP" |
|
|
959 |
}, |
|
|
960 |
"source": [ |
|
|
961 |
"#10, 2\n", |
|
|
962 |
"\n", |
|
|
963 |
"```\n", |
|
|
964 |
"bleu --> 0.057428091668584556\n", |
|
|
965 |
"rouge1 --> 0.20646246870472995\n", |
|
|
966 |
"rouge2 --> 0.10519838762813453\n", |
|
|
967 |
"rougel --> 0.1950256050028359\n", |
|
|
968 |
"```" |
|
|
969 |
] |
|
|
970 |
}, |
|
|
971 |
{ |
|
|
972 |
"cell_type": "markdown", |
|
|
973 |
"metadata": { |
|
|
974 |
"id": "wkQtE2rArKnM" |
|
|
975 |
}, |
|
|
976 |
"source": [ |
|
|
977 |
"# 10, 5\n", |
|
|
978 |
"\n", |
|
|
979 |
"```\n", |
|
|
980 |
"bleu --> 0.028692153647818627\n", |
|
|
981 |
"rouge1 --> 0.21279947143169525\n", |
|
|
982 |
"rouge2 --> 0.1004407817858144\n", |
|
|
983 |
"rougel --> 0.20142881253757677\n", |
|
|
984 |
"```" |
|
|
985 |
] |
|
|
986 |
}, |
|
|
987 |
{ |
|
|
988 |
"cell_type": "markdown", |
|
|
989 |
"metadata": { |
|
|
990 |
"id": "Nvfq3joB6AgT" |
|
|
991 |
}, |
|
|
992 |
"source": [ |
|
|
993 |
"# ktrapeznikov/albert-xlarge-v2-squad-v2 + Fine Tuned Bert on (Squad + Our Dataset)" |
|
|
994 |
] |
|
|
995 |
}, |
|
|
996 |
{ |
|
|
997 |
"cell_type": "markdown", |
|
|
998 |
"metadata": { |
|
|
999 |
"id": "cvTGLrvqARNL" |
|
|
1000 |
}, |
|
|
1001 |
"source": [ |
|
|
1002 |
"# 3, 2\n", |
|
|
1003 |
"\n", |
|
|
1004 |
"```\n", |
|
|
1005 |
"bleu --> 0.0700302475143219\n", |
|
|
1006 |
"rouge1 --> 0.2025044353996794\n", |
|
|
1007 |
"rouge2 --> 0.11069682602623314\n", |
|
|
1008 |
"rougel --> 0.1903201590307057\n", |
|
|
1009 |
"```" |
|
|
1010 |
] |
|
|
1011 |
}, |
|
|
1012 |
{ |
|
|
1013 |
"cell_type": "code", |
|
|
1014 |
"metadata": { |
|
|
1015 |
"id": "NsMM-t20CsPz" |
|
|
1016 |
}, |
|
|
1017 |
"source": [ |
|
|
1018 |
"" |
|
|
1019 |
], |
|
|
1020 |
"execution_count": null, |
|
|
1021 |
"outputs": [] |
|
|
1022 |
} |
|
|
1023 |
] |
|
|
1024 |
} |