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How to freeze all layers of Bert and just train task-based layers during the fine-tuning process?
We can do it by setting the `requires_grad=false` for all layers In pytorch-pretrained-BERT. But is t…
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I have been using pre-trained cross-encoder/ms-marco-MiniLM-L-6-v2 on a dataset similar to MS-MARCO for re-ranking paragraphs based on a query/question. The top-3 accuracy results have been pretty goo…
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We are a group of NYU MS in Data Science students who are working on developing an end-to-end speech-to-intent model. We have read your paper and replicated your code and would love to ask you some qu…
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Add a support for deberta model "MoritzLaurer/deberta-v3-large-zeroshot-v1.1-all-33". This model is heavily used for text classification.
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When I convert BERT (pytorch model) to onnx format (without any optimizations) and then try to run the "symbolic_shape_infer.py" script with the obtained onnx model as an input argument, I get the fol…
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Hi @savasy, thank's for your great work on those tasks, do you have some plans for fine tuning bert on the [POS](https://github.com/mrm8488/shared_colab_notebooks/blob/master/fine_tuning_on_UDPOS_Engl…
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Thank you for your implementation. I encountered difficulties while attempting to apply PBRF to the final layer (linear) when fine-tuning a BERT model for text classification. Would it be possible for…
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I'm able to train a classification model using a pretrained LM using the following parameters:
```python
tokenizer = BertTokenizer.from_pretrained('bert-base-multilingual-uncased', do_lower_case=T…
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Which script is used for BERT training benchmark, I see there are 2 kind of script, one is for pre-train, e.g train.py, the other is for fine tuning, e.g. run_classify.py.
Which one is used for bench…
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`run_classifier.R` is mostly about fine-tuning BERT with a classifier head. RBERT is not quite working at this level yet. There are almost certainly bugs that would prevent this from working in the pr…