Oh, and good job starting your reference with an author that goes early in the alphabetical ordering, lol:

Or we could do
@misc{clearml, title = {ClearML - Your entire MLOps stack in one open-source tool}, year = {2019}, note = {Software available from }, url={ }, author = {Allegro AI}, }

¯_(ツ)_/¯

I suppose the flow would be something like:
select all experiments from project x with iterations greater than y, pull runtime for each one add them all up. I just don't know what API calls to make for 1 and 2

I might not be able to get to that but if you create an issue I'd be happy to link or post what I came up with, wdyt?

It seems to create a folder and put things into it, I was hoping to just observe the tensorboard folder

What I'm curious about is how clearML hooks into that to know to upload the other artifacts such as http://optimizer.pt .

lol TIL: https://stackoverflow.com/questions/5626193/what-is-monkey-patching

Yes, it trains fine. I can even look at the console output

Local in the sense that my team member set it up, remote to me

Sure, I can give that a try!

Hello! integration in what sense? Training a model? Uploading a model to the hub? Something else?

It's not a big deal because it happens after I'm done with everything, I can just reset the Colab runtime and start over

This seems to work:

` from clearml import Logger
for test_metric in posttrain_metrics:
print(test_metric, posttrain_metrics[test_metric])

#report_scalar(title, series, value, iteration)
Logger.current_logger().report_scalar("test", test_metric, posttrain_metrics[test_metric], 0) `

No, they're not in Tensorboard

OK, I guess
` training_args_dict = training_args.to_dict()

Task.current_task().set_parameters_as_dict(training_args_dict) `works, but how to change the name from "General"?

Actually at this point, I'd say it's too late, you might want to just generate new credentials...

Martin I found a different solution (hardcoding the parent tasks by hand), but I'm curious to hear what you discover!

Long story, but in the other thread I couldn't install the particular version of transformers unless I removed it from "Installed Packages" and added it to setup script instead. So I took to just throwing in that list of packages.

IrritableOwl63 pm'd you a task ID

Yup! That works.
from joeynmt.training import train train("transformer_epo_eng_bpe4000.yaml")And it's tracking stuff successfully. Nice

not much different from the HuggingFace version, I believe

Here's the actual script I'm using

Oh, that's a neat tip! I just set that in the Task settings? I didn't know that was possible

Reproduce the training:
# How to run `

You need to pip install requirements first. I think the following would do: transformers datasets clearml tokenizers torch

CLEAR_DATA has train.txt and validation.txt, the .txt files just need to have text data on separate lines. For debugging, anything should do.

For training you need tokenizer files as well, vocab.json, merges.txt, and tokenizer.json.

you also need a config.json, should work.

export CLEAR_DATA="./data/dataset_for...

Hmm, I tried publishing one and it doesn't seem to have worked quite that easily: https://app.pro.clear.ml/projects/b4a1875539cb4d9798529439801402ee/experiments/6f4cb4718c7c4a25b3a041c63f6ff2b4/execution?columns=selected&columns=type&columns=last_iteration&columns=hyperparams.Args.num_train_epochs&columns=name&columns=status&columns=users&columns=started&columns=last_update&columns=tags&columns=parent.name&columns=project.name&columns=m.2eed1fe0db36d674643b5f84d2adf46e.06eaeb413e7213cb8b5419...

I gather there's a distinction between the two, with app.clear being the public cloud-based SaaS version

Right now it's on https://app.pro.clear.ml/ , yeah

Ah... so there actually is a way to share it then, so long as people are signed up? How would one do this? Do I just share a link to the experiment, like https://app.pro.clear.ml/projects/b4a1875539cb4d9798529439801402ee/experiments/6f4cb4718c7c4a25b3a041c63f6ff2b4/output/execution?columns=selected&columns=type&columns=last_iteration&columns=hyperparams.Args.num_train_epochs&columns=name&columns=status&columns=users&columns=started&columns=last_update&columns=tags&columns=parent.name&colum...

Is it based on the ClearML serversion?