Thilina Rajapakse

Sorry, I am not sure why this is happening. I recommend that you try the Simple Transformers library as it supports multi-gpu training by default and I have used multi-gpu...

The code in this repo was not written to support multi-GPU training (mainly because I only have the one). But, the code that this is [based on](https://github.com/huggingface/transformers/blob/master/examples/run_glue.py) does support multi-GPUs....

You can get the training loss without any changes. You can use `tensorboardx` to get a graph of the training loss. The loss information is being written to the 'runs'...

There should be a subdirectory inside runs for every training run. So your command would look like `tensorboard --logdir=runs/subdirectory`. To visualize the last run, you can use the line below....

Great to see you got it to work. I didn't realize you were on Colab!

This repo is no longer actively maintained. Please use [Simple Transformers](https://github.com/ThilinaRajapakse/) instead.

The recommended method is to get the code from the Github repo since the code on the article is for demonstration only. I do understand that sometimes you just want...

Hope it goes well!

It looks like your Pytorch is out of date. Can you update it and try again?

Unfortunately, with no GPU your training speed will be _slow_. I can't remember the total number of steps, but it should be there in the output right before training starts....