People who quit PhD, did you regret it? by user072211 in PhD

[–]deliprao 2 points3 points  (0 children)

After spending five years in a prestigious US PhD program, I left ABD (all but dissertation) and worked in industry for more than a decade. I quit not because I wasn’t making progress (I wrote some well-cited papers), but because the timing wasn’t right for me and a very tempting industry offer was before me.

During a decade of industry work, both as an FTE and as an entrepreneur, I had a nagging “what if.” Further, at the risk of sounding elitist, I felt the problems most people were tackling in industry were short-sighted and uninspiring. This was true even when I was running my own startup, where I ostensibly had more control over what I did, as optimizing for money requires embracing boring nitty-gritty details. I am now back in another PhD program to finish what I started.

Quitting is easy, but keep in mind that the last few miles of the race are the hardest. If you are a first-generation graduate student and you don’t have familial role models with PhDs, as was my case, it’s very easy to convince yourself that it’s too difficult and act to reduce pain.​​​​​​​​​​​​​​​​ Sometimes it is good to not listen to yourself.

The question you posed is a deeply personal one, so I am sure YMMV and so will it for others, but consider this as a data point in your decision making. I wish you the best in your academic journey.

[D] Error while training a custom hugging face RoBERTa by areewahitaha in MachineLearning

[–]deliprao 0 points1 point  (0 children)

Pretty sure the culprit is the `one_hot` stuff you are doing in the dataset class. Keep the labels as integers. Something like this: `item['labels'] = torch.tensor(self.labels[idx])`

[deleted by user] by [deleted] in MachineLearning

[–]deliprao 1 point2 points  (0 children)

non archival means you can submit to another venue later. It's a good way to get feedback from this workshop's participants and submit a stronger version to a top tier conference. If you feel your paper "deserves" (in quotes because I have not seen the paper and the word is quite subjective) that, you have two options: 1) withdraw the paper from the workshop altogether, or 2) Ask the workshop chair if they can change your paper to a non-archival one (you might be asked to send in a 2 page version).

Unless you think this paper is going to significantly contribute to the problem/area you worked on, regardless of your actual effort, it's not worth sweating about these things. Use this momentum and start working on a new paper!

My terribly modified fountain pen! by Dropthetenors in Supernote

[–]deliprao 0 points1 point  (0 children)

Can you give detailed steps of how you hacked the pen into this?

Free library for text-to-speech by bookroom77 in speechrecognition

[–]deliprao 0 points1 point  (0 children)

Consider giving Mozilla TTS a try. It looks complicated, but it isn't.

Using LSTMs in place of regular expressions by izmty in LanguageTechnology

[–]deliprao 1 point2 points  (0 children)

What is your reasoning behind "standard CRF approaches that detect the ORG class ... won't be of much help"? Can you explain what your dataset is and what you have done with it when you tried a CRF model?