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Based on the Pytorch-Transformers library by HuggingFace. To be used as a starting point for employing Transformer models in text classification tasks. Contains code to easily train BERT, XLNet, RoBER...

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Hi, When I run your code on multi-gpu, performance degrades severely (compared to the single-gpu version). To make the code multi-gpu competable, I've only added 2 lines of code: *...

I am getting this error when I run: `if args['do_train']: train_dataset = load_and_cache_examples(task, tokenizer) global_step, tr_loss = train(train_dataset, model, tokenizer) logger.info(" global_step = %s, average loss = %s", global_step, tr_loss`...

if args['do_train']: train_dataset = load_and_cache_examples(task, tokenizer) global_step, tr_loss = train(train_dataset, model, tokenizer) logger.info(" global_step = %s, average loss = %s", global_step, tr_loss) I still get this error when running this...

Is there any specific parameter that we should pass to run the utils.py? Running the file itself seems does nothing. It does not create the InputFeature objects or anything. What...

Hi, I would like to know if the model over-fits and also the optimum number of epochs, plotting accuracy and loss as it's shown [here](https://stackoverflow.com/questions/41908379/keras-plot-training-validation-and-test-set-accuracy). It would be possible to...

Hello! The following import line is missing from the Gist you provided in your article. Discovered it was missing when I got an error running the code. I found it...

I have two GPUs (2 x NVIDIA Tesla V100) and I'm running the codes in `run_model.ipynb` on Google Cloud. I get the CUDA out of memory exception when I want...

Thanks to your help - I have added custom losses, special initialization and a bunch of other things as extensions. I am now trying to mess with the sentence classification...

Hi, I downloaded and ran your program, and got a training error as above. I have no GPU, so I changed the setup to fp16 = 'false' (xlnet left as...

1. replacing every pytorch_transformers by transformers fixes the problem of giving negative dimensions to create tensor. 2. fp 16 requires nv apex, but can you write something to note that...