Is there any dataset for fake news (different from sentiment analysis) detection? I have one NELA-GT but then I would need to pre-train that from scratch?
Any methods, am I on the correct page ? https://huggingface.co/transformers/training.html
I want to use BERT model,
thanks
You could try to get baseline with fine-tuning before going for pre-training and then make decision based on the results.
This thread has nice pointer for pre-training
BERT has been trained on MLM and NSP objective. I wanted to train BERT with/without NSP objective (with NSP in case suggested approach is different). I haven’t performed pre-training in full sense before. Can you please share how to obtain the data (crawl and tokenization details which were used) on which BERT was trained on ?. Since it takes a lot of time, I am looking for well tested code that can yield the BERT with/without NSP in one go. Any suggestions will be helpful.
I know about some pr…
1 Like
thanks, so it seems I need to know the difference between pre-training and fine-tuning?
This resources should help
Discussions:
Hacker News (98 points, 19 comments), Reddit r/MachineLearning (164 points, 20 comments)
Translations: Chinese (Simplified), French 1, French 2, Japanese, Korean, Persian, Russian, Spanish
2021 Update: I created this brief and highly...
thanks , yours information is always very useful
if I am correct, the pre-training on any corpus is unsupervised, by that I mean the text is large amount without any labels, however in fine-tuning, we should have labels?
Yes, in modern nlp, the models are pre-trained using unspervised objective (maksed lanaguge modeling, auto-regressive LM, document denosing etc).
And the downstream tasks (classification, QA) etc are supervised. Again, the above resources should help you understand the difference better.
1 Like
@valhalla thanks, you have so much knowledge, thanks for sharing with newbies.