Research workshop on large language models - The Summer of Language Models 21
At the moment we have 2 code repos:
Currently, the most active segments of this repo are:
We have READMEs for specific aspects, such as:
While we keep detailed chronicles of experiments and findings for some of the main trainings, here is a doc that contains a summary of the most important findings: Lessons learned
You can watch the training logs live by running this tail -f
like script over remote log file that gets synced to the hub once an hour:
perl -e '$u=shift; $b=0; while(1){($e)=qx[curl -sI $u]=~/content-length: (d+)/;
print qx[curl -sr $b-$e -L $u] if $e>$b; $b=$e; sleep 300}'
https://huggingface.co/bigscience/tr1-13B-logs/resolve/main/main_log.txt
Architecture and scaling baseline runs: no fancy tricks, just GPT2. Here are links to the respective tensorboards:
Size | 1B3 | 760M | 350M | 125M |
---|---|---|---|---|
C4 + low warmup | a | b | c | |
OSCAR + low warmup | f | |||
C4 + high warmup | e | |||
OSCAR + high warmup | d (current baseline) | g | h | i |
Pile + high warmup | m | j | k | l |
104B - unmodified Megatron gpt2 - with extra-wide hidden size to learn how to deal with training instabilities
You can watch the training logs live by running this tail -f
like script over remote log file that gets synced to the hub once an hour:
perl -e '$u=shift; $b=0; while(1){($e)=qx[curl -sI $u]=~/content-length: (d+)/;
print qx[curl -sr $b-$e -L $u] if $e>$b; $b=$e; sleep 300}'
https://cdn-lfs.huggingface.co/bigscience/tr8-104B-logs/b2cc478d5ae7c9ec937ea2db1d2fe09de593fa2ec38c171d6cc5dca094cd79f9
This is the current main training
tr11-176B-ml
You can watch the training logs live by running this tail -f
like script over remote log file that gets synced to the hub once an hour:
perl -e '$u=shift; $b=0; while(1){($e)=qx[curl -LsI $u]=~/2 200.*?content-length: (d+)/s;
print qx[curl -Lsr $b-$e $u] if $e>$b; $b=$e; sleep 300}'
https://huggingface.co/bigscience/tr11-176B-ml-logs/resolve/main/logs/main/main_log.txt