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Incrementally Train BERT with minimum QnA records - to get improved results
Machine Learning models in production environmentClarification wanted for make_step function of Google's deep dream scriptBest approach for image recognition/classification with few training dataMLPClassifier threshold factor to eliminate test samples that are not in match with train dataTools and Techniques for Analyzing German Automotive Discussion Forum PostsHow to train and validate a model continously which affects its own future data?Training dataset decreasing in quality (Google data science blog)Understanding why my binary classification is approaching 50% accuracy using TensorFlow and KerasHyper-parameter tuning when you don't have an access to the test dataIssues with training SSD on own dataset
$begingroup$
We are using Google BERT for Question and Answering. We have fine tuned BERT with SQUAD QnA release train data set (https://github.com/google-research/bert , https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json)
It generated new checkpoints and BERT is giving good answers for most of questions we asked on our text documents. However, there are some questions which it is answering wrong, so we are trying to further fine tune with our Question and known answer on our text document. We further trained based on last generated checkpoint and got new checkpoint.
With new checkpoint when we are asking the same question, the answer did not got corrected! Previously BERT was giving wrong answer with 99% confidence and now also giving same wrong answer with 95% confidence.
Can someone suggest, if they have same or similar experience, and suggest please.
Following are questions in BERT github Issues, and are unanswered for quite some time:
- BERT accuracy reduced after providing custom training..The answer is
also not correct : https://github.com/google-research/bert/issues/492 - Unable to incrementally train BERT with custom training: https://github.com/google-research/bert/issues/482
- Little training has no impact: https://github.com/google-research/bert/issues/481
- Custom Domain Training: https://github.com/google-research/bert/issues/498
machine-learning training transformer bert
$endgroup$
add a comment |
$begingroup$
We are using Google BERT for Question and Answering. We have fine tuned BERT with SQUAD QnA release train data set (https://github.com/google-research/bert , https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json)
It generated new checkpoints and BERT is giving good answers for most of questions we asked on our text documents. However, there are some questions which it is answering wrong, so we are trying to further fine tune with our Question and known answer on our text document. We further trained based on last generated checkpoint and got new checkpoint.
With new checkpoint when we are asking the same question, the answer did not got corrected! Previously BERT was giving wrong answer with 99% confidence and now also giving same wrong answer with 95% confidence.
Can someone suggest, if they have same or similar experience, and suggest please.
Following are questions in BERT github Issues, and are unanswered for quite some time:
- BERT accuracy reduced after providing custom training..The answer is
also not correct : https://github.com/google-research/bert/issues/492 - Unable to incrementally train BERT with custom training: https://github.com/google-research/bert/issues/482
- Little training has no impact: https://github.com/google-research/bert/issues/481
- Custom Domain Training: https://github.com/google-research/bert/issues/498
machine-learning training transformer bert
$endgroup$
add a comment |
$begingroup$
We are using Google BERT for Question and Answering. We have fine tuned BERT with SQUAD QnA release train data set (https://github.com/google-research/bert , https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json)
It generated new checkpoints and BERT is giving good answers for most of questions we asked on our text documents. However, there are some questions which it is answering wrong, so we are trying to further fine tune with our Question and known answer on our text document. We further trained based on last generated checkpoint and got new checkpoint.
With new checkpoint when we are asking the same question, the answer did not got corrected! Previously BERT was giving wrong answer with 99% confidence and now also giving same wrong answer with 95% confidence.
Can someone suggest, if they have same or similar experience, and suggest please.
Following are questions in BERT github Issues, and are unanswered for quite some time:
- BERT accuracy reduced after providing custom training..The answer is
also not correct : https://github.com/google-research/bert/issues/492 - Unable to incrementally train BERT with custom training: https://github.com/google-research/bert/issues/482
- Little training has no impact: https://github.com/google-research/bert/issues/481
- Custom Domain Training: https://github.com/google-research/bert/issues/498
machine-learning training transformer bert
$endgroup$
We are using Google BERT for Question and Answering. We have fine tuned BERT with SQUAD QnA release train data set (https://github.com/google-research/bert , https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v1.1.json)
It generated new checkpoints and BERT is giving good answers for most of questions we asked on our text documents. However, there are some questions which it is answering wrong, so we are trying to further fine tune with our Question and known answer on our text document. We further trained based on last generated checkpoint and got new checkpoint.
With new checkpoint when we are asking the same question, the answer did not got corrected! Previously BERT was giving wrong answer with 99% confidence and now also giving same wrong answer with 95% confidence.
Can someone suggest, if they have same or similar experience, and suggest please.
Following are questions in BERT github Issues, and are unanswered for quite some time:
- BERT accuracy reduced after providing custom training..The answer is
also not correct : https://github.com/google-research/bert/issues/492 - Unable to incrementally train BERT with custom training: https://github.com/google-research/bert/issues/482
- Little training has no impact: https://github.com/google-research/bert/issues/481
- Custom Domain Training: https://github.com/google-research/bert/issues/498
machine-learning training transformer bert
machine-learning training transformer bert
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