Comments (5)
given that you have a significantly good amount of training data, i believe this could be a really good endevour as the DebERTa-v3 architecture and training procedure is insanely great. good h-param search and a nice continual pretraining should give great results. do let me know how it goes.
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Would I use the deberta-v3-X-continue in rtd.sh or pretrain a model from scratch using my dataset?
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do continual pretraining, i mean use the deberta-v3-X-continue. all medical domain LM are a result of continual pretraining
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Hi all, I am in the exact same boat here. What is that rtd.sh is mentioned? I mean I know is a bash file but where is it ? Would be nice to see a python script that shows how the domain adaptation should be run and how to save the model.
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do continual pretraining, i mean use the deberta-v3-X-continue. all medical domain LM are a result of continual pretraining
Hi, @StephennFernandes. How are you doing? Have you managed to sucessfully pretrain or continue pretraining a deberta V3 model in another language? Back when we were talking, my discriminator couldnt get better.
Best regards, Fabio.
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Related Issues (20)
- Error when running the example code for pretraining the rtd model. HOT 15
- No module named 'torch._six' HOT 2
- AssertionError: RTD is not registed. HOT 1
- n/a
- Deberta-v3-base Generator model HOT 2
- Load deberta-v3-large but got deberta-v2 model HOT 2
- Install fails due to use of deprecated `sklearn` package
- Eligibility for Commercial Use HOT 1
- When calculating Qr, why is the W of content used instead of the W of position used?
- Trying to run rtd_task.py on Windows HOT 1
- EOF error while running the rtd.sh script HOT 1
- Trying to initialize model "large"
- Question regarding symmetric KL Loss
- Model is not initialized correctly when path to a pretrained model is provided via `pre_trained`
- Inference gives different results when using multiple gpus (distributed mode) vs just one gpu (not distributed mode)
- No assert: Training does not start when using different tokenizer/ tokenized-data
- Reason for missing values in table for the Roberta-base, mrpc entry
- How can I evaluate COPA dataset?
- Generator weights
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