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Amazing work ^^ and thanks for your beautiful codes, I can easily reproduce the results. However, I got a small question, since the results in STS are reported averagly, how can I see the performance …
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When I run this piece of code
```
from transformers import T5Tokenizer
from sentence_transformers.models import Transformer, Pooling
from sentence_transformers import SentenceTransformer
tokenize…
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Hi, I tried running the script in this repo with the following command
```bash
export CUDA_VISIBLE_DEVICES="1" && bash run_unsup_example.sh
```
after the model is trained, the automatic evaluat…
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I am wondering how can I reproduce the pre-trained models. For example, I think "stsb-mpnet-base-v2" is trained on "ALLNLI" and "STSb" dataset with "MultipleNegativesRankingLoss". Is it right?
Also…
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Thanks for the repository and for continuous updates.
Wanted to check if understood it correctly:
Is it possible to continue fine-tuning one of the multilingual models for a specific domain?
F…
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When i run run_unsup_example.sh, an error happend:
6%|████████▎ | 125/1954 [01:3…
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I am trying to finetune to extract more information from BERT model. Can I use SentenceTransformer for returning token_embbedings and apply sentence_transformers.models.CNN as TextCNN on this token em…
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tried to use albert-xlarge-v2 with train_batch_size 16 on stsbenchmark, training_stsbenchmark.py
for the dev evaluation, consine similarity is nan, looks the outputs are closed to constants.
pleas…
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Hello, and thank you for this useful code! I tried to reproduce the unsupervisd BERT+SimCSE results, but failed. My environment setup is as follows:
- pytorch=1.7.1 (I also tested 1.8.0)
- cudatoolk…
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http://ixa2.si.ehu.eus/stswiki/images/4/48/Stsbenchmark.tar.gz
我从这里下载的,发现数据处理略有问题。