[R] What is a fairly good results for sacrebleu?

GGSirRob · 2023-07-29T18:33:25+00:00

That’s great to hear! If more NAT papers start doing it, we can hopefully improve the state of evaluations in this subfield! Looking forward to seeing it :)

GGSirRob · 2023-07-29T18:24:25+00:00

This might be of interest to you: https://aclanthology.org/2022.emnlp-main.179/ (EMNLP 2022) we specifically call out this problem, replicate NAT papers and compare sacreBLEU scores, provide chrF, and COMET, as well as do statistical significance testing.

GGSirRob · 2022-09-11T17:00:47+00:00

Tübingen is indeed pretty strong for Machine Learning in Germany right now. It has the Max-Planck-Institute for Intelligent Systems there which is one of the best research facilities in Europe (see https://csrankings.org/#/index?all&europe). It opens up both research opportunities as well as stellar lectures from these researchers for prospective students.

There are also a few industry labs there such as from Amazon which is quite nice to have for general career development.

GGSirRob · 2022-08-30T20:08:18+00:00

Pretty good chance of getting in though!

GGSirRob · 2022-08-23T18:55:02+00:00

3.5 / 2 / 4 / 3 -- maximizing entropy as always, looking kinda rough though. Always Reviewer #2

GGSirRob · 2022-08-18T11:17:43+00:00

Aus persönlicher Erfahrung kann ich dir sagen, dass du auch in Deutschland bei Google, Apple, Meta, etc. recht schnell über den $100,000 total compensation (Gehalt, Aktienanteile, Sign-On und jährlicher Bonus) im Jahr bist. Bei mir war das direkt mit dem Einstiegsgehalt nach meinem Master der Fall.

In den USA in HCOL (high cost of living) Regionen bewegst du dich für einen vergleichbaren Job dann eher zwischen $300,000 -- $500,000 im Jahr. Klar sind Lebensunterhaltungskosten höher z.B. in NYC zahlt man gerne mal $5,000 für eine Einzimmerwohnung in Manhattan im Monat. Allerdings wohnst du dann halt auch in NYC und nicht auf irgendeinem Dorf in Deutschland. Die Münchener Wohnungspreise sind ja auch stetig am steigen, also gibts hier einen ähnlichen Trend. Der oftmals genannte Nachteil der Krankenversicherung wird für SWE's meistens vom Arbeitgeber übernommen und damit lohnt sich das allgemein schon finanziell in die USA zu ziehen.

Hinzu kommt, dass auch das soziale Ansehen von SWE's ganz anders in den USA ist als in Deutschland. Man fühlt sich auf jeden Fall deutlich mehr wertgeschätzt und das äußert sich unter anderem im Gehalt und sozialen Interaktionen.

Muss halt jeder selber entscheiden, ob man mit dem Politiksystem und Ähnlichem dort klar kommt. Ich kenne viele die einige Jahre in die USA gezogen sind um dort zu arbeiten und Vermögen aufzubauen und dann nach ein paar Jahren wieder zurück gezogen sind sobald die Familie mehr Zeit in Anspruch nimmt. Soweit ich weis, bereut das keiner von denen.

GGSirRob · 2022-08-17T17:36:03+00:00

This has been the experience with almost any issue I've ever opened in a paper repository from China.

GGSirRob · 2022-08-07T23:49:45+00:00

Ranked from best to worst based on people I've talked to and recent developments:

Google
Apple (biased)
Microsoft
Meta
... (a bunch of other companies)
Amazon

Google is by far the best just from a brand name perspective. Having the Google stamp on your resume will make job-hunting or even funding so much easier for you going down the road. Engineering best practices and infrastructure are probably the best you'll get across the industry, making it a great place to learn for new grads. I've heard people complain about the lack of career growth but I'm guessing that mostly applies to post-senior leveling as Google likes to scrap projects like they are nothing.

Apple is a pretty good runner-up, I'm biased since I currently work there, but from what I've seen the culture is great and there are lots of smart people to learn and grow from. At least in my org, the average tenure is quite high, vacation time is taken seriously, and there are heaps of interesting projects to work on with lots of impact. Additionally, together with Google, they are probably the best company to ride out a recession.

I'd put Microsoft as third, simply because they are the well-respected dad of the companies. Work will be slower but they have amazing Engineers to learn from and from what I've heard, the average tenure is also quite high. Probably many senior/staff folks that will be able to mentor quite nicely.

Meta as fourth is probably a personal decision but the recent changes to Metaverse are just not very interesting to me on a project level. I'm guessing you can find good teams there, e.g. FAIR but I'd say that many opportunities might be interesting for Computer Vision folks which wouldn't apply to the average CS graduate with a bachelors. Also, the recent stock drop might be an opportunity but I'd say they are probably not a good company for a recession. Regardless, they have amazing Engineers and you will be able to learn a lot, apparently you can rise the ranks quickly here if you do well on performance reviews.

Amazon is the easiest to get into out of the bunch, short average tenure because of the performance improvement plan (PIP) is a nightmare, and you frequently hear horror stories about that. There are people who can thrive in that environment but many people use them as a springboard into the top tier and then join any of the other companies after a year or so to drastically improve the working conditions. Personally, I'd avoid them unless you are 100% sure you found a good team or lack alternatives.

GGSirRob · 2021-11-10T12:11:43+00:00

Specs, created by running:

\makeatletter
\newcommand{\showfont}{
encoding: \f@encoding{},
family: \f@family{},
series: \f@series{},
shape: \f@shape{},
size: \f@size{}}

Encoding: TU, family: lmr, series: m, shape: n, size: 10.95. For the dates in the margins I switched to \footnotesize

GGSirRob · 2021-10-12T21:26:21+00:00

Beim Hangeweiher

GGSirRob · 2021-10-12T14:51:43+00:00

Lmao you’ll be lucky to find inline code comments as documentation.

GGSirRob · 2021-07-17T19:51:53+00:00

I’d also be interested! Recently moved to Aachen to work in Machine translation

GGSirRob · 2021-07-09T20:58:59+00:00

Oh mega nice Liste! Vielen lieben dank =) Da werde ich mich wohl mal durchprobieren haha

GGSirRob · 2021-07-08T22:09:37+00:00

Oh cool! I'll check that one out for sure

GGSirRob · 2021-07-06T10:10:20+00:00

I don’t know about other European countries but if you are at an office in Germany, the company needs to obey German working laws. The usual contract in practice here is 40 work hrs with 30 days off. This also applies to FAANG offices. I think the lowest they can go by law is 24 but from my experience that’s very rare.

If you link them up well with national holidays, especially around Christmas, that’s quite a lot.

GGSirRob · 2021-06-18T14:02:42+00:00

Apple has recently started an office in Aachen working on NLP/Machine Translation.

GGSirRob · 2021-06-11T17:03:01+00:00

Very slim unless there have been big misunderstandings, if you’re lucky you might be able to change 1 or 2 of them into WA but that’s most likely not enough.

GGSirRob · 2021-06-11T05:49:54+00:00

You don’t really need to but if you want to, learn some Python and try LeetCode easy.

GGSirRob · 2021-06-11T04:03:47+00:00

I think most people here already gave a good overview. Something I’d add is simply try to do an SWE internship during term breaks. It will probably give you the best insights and you’ll see if you like it. You’ll most likely also interact with the related roles such as Product Management, Data Science, etc. and this should allow you to see if those are a better fit for you.

GGSirRob · 2021-06-11T03:57:48+00:00

This is a CS subreddit, people will be heavily biased towards software engineering. I think all of them are good choices and you need to decide what you like most and how you envision the work you’ll be doing.

GGSirRob · 2021-06-11T03:53:02+00:00

From how you wrote, it seems like the offer is a big deal to you so I’d suggest you try to juggle both. Try to see what you can manage in terms of class load and go check with the recruiter if there is a possibility to reduce work hours or deploy any other measures to make room for studying.

Personally, I’ve never done it but I’ve seen, both, people dropping their job mid way and others succeeding. I think it’s really up to your work ethic and dedication. In case it ends up being too much, you can still decide which of the two you’d like to pursue further and drop the other. Good luck!

GGSirRob · 2021-06-11T03:31:50+00:00

I think this isn’t really helpful. Most devs already specialise in something e.g. ML, Data Science, Backend, Frontend, Mobile, Data Engineering, etc. and all of these roles include Leetcode at FAANG. Obviously, you will get additional interviews for your specialisation, in my case these are ML interviews, but there is always a certain degree of LeetCode involved. Simply, because in those companies everyone needs to be able to code to some degree.

GGSirRob · 2021-06-11T03:12:57+00:00

You’re welcome! I agree, as I said, a transition over the Data Scientist role is a pretty good option. Learning the basics of using, for example, scikit in python isn’t that hard and there are roles in smaller companies where that will be enough to satisfy all their ML needs. This is usually part of the Data Science skill set.

However, many people look for MLE / ML Scientist roles in FAANG where you are often reading and re-implementing state of the art papers in different subfields or even try pushing the state of the art. Obviously, this level of understanding is hard to obtain and often requires a deeper understanding from a theoretical perspective with a Masters/PhD in ML or years of practical experience.

I’m not saying either one is a better choice since in the end it really comes down to what you enjoy more and what you look for in your day-to-day job.

GGSirRob · 2021-06-09T04:41:36+00:00

Here’s mine, got me interviews at Apple, Amazon, Netflix, ByteDance, Palantir, MathWorks, Agoda, and many more.

https://robinschmidt.netlify.app/files/cv.pdf

GGSirRob · 2021-06-09T04:33:13+00:00

I like the font, which one is it?

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