| # Turkish QNLI Model | |
| I fine-tuned Turkish-Bert-Model for Question-Answering problem with Turkish version of SQuAD; TQuAD | |
| https://huggingface.co/dbmdz/bert-base-turkish-uncased | |
| # Data: TQuAD | |
| I used following TQuAD data set | |
| https://github.com/TQuad/turkish-nlp-qa-dataset | |
| I convert the dataset into transformers glue data format of QNLI by the following script | |
| SQuAD -> QNLI | |
| ``` | |
| import argparse | |
| import collections | |
| import json | |
| import numpy as np | |
| import os | |
| import re | |
| import string | |
| import sys | |
| ff="dev-v0.1.json" | |
| ff="train-v0.1.json" | |
| dataset=json.load(open(ff)) | |
| i=0 | |
| for article in dataset['data']: | |
| title= article['title'] | |
| for p in article['paragraphs']: | |
| context= p['context'] | |
| for qa in p['qas']: | |
| answer= qa['answers'][0]['text'] | |
| all_other_answers= list(set([e['answers'][0]['text'] for e in p['qas']])) | |
| all_other_answers.remove(answer) | |
| i=i+1 | |
| print(i,qa['question'].replace(";",":") , answer.replace(";",":"),"entailment", sep="\t") | |
| for other in all_other_answers: | |
| i=i+1 | |
| print(i,qa['question'].replace(";",":") , other.replace(";",":"),"not_entailment" ,sep="\t") | |
| ``` | |
| Under QNLI folder there are dev and test test | |
| Training data looks like | |
| > 613 II.Friedrich’in bilginler arasındaki en önemli şahsiyet olarak belirttiği kişi kimdir? filozof, kimyacı, astrolog ve çevirmen not_entailment | |
| > 614 II.Friedrich’in bilginler arasındaki en önemli şahsiyet olarak belirttiği kişi kimdir? kişisel eğilimi ve özel temaslar nedeniyle not_entailment | |
| > 615 Michael Scotus’un mesleği nedir? filozof, kimyacı, astrolog ve çevirmen entailment | |
| > 616 Michael Scotus’un mesleği nedir? Palermo’ya not_entailment | |
| # Training | |
| Training the model with following environment | |
| ``` | |
| export GLUE_DIR=./glue/glue_dataTR/QNLI | |
| export TASK_NAME=QNLI | |
| ``` | |
| ``` | |
| python3 run_glue.py \ | |
| --model_type bert \ | |
| --model_name_or_path dbmdz/bert-base-turkish-uncased\ | |
| --task_name $TASK_NAME \ | |
| --do_train \ | |
| --do_eval \ | |
| --data_dir $GLUE_DIR \ | |
| --max_seq_length 128 \ | |
| --per_gpu_train_batch_size 32 \ | |
| --learning_rate 2e-5 \ | |
| --num_train_epochs 3.0 \ | |
| --output_dir /tmp/$TASK_NAME/ | |
| ``` | |
| # Evaluation Results | |
| == | |
| | acc | 0.9124060613527165 | |
| | loss| 0.21582801340189717 | |
| == | |
| > See all my model | |
| > https://huggingface.co/savasy | |