Update README.md

README.md

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 - STS : seed=111,epoch=10, lr=1e-4, eps=1e-6, warm_step=10%, max_seq_len=128, train_batch=128(small 모델=32) (albert 13m/7G) [훈련코드](https://github.com/kobongsoo/BERT/blob/master/sbert/cross-encoder/sbert-corossencoder-train-nli.ipynb) 
 - NLI  훈련 : seed=111,epoch=3, lr=3e-5, eps=1e-8, warm_step=10%, max_seq_len=128, train_batch=64, eval_bath=64(albert 2h/7G) [훈련코드](https://github.com/kobongsoo/BERT/blob/master/sbert/cross-encoder/sbert-corossencoder-train-sts.ipynb) 
 - [평가코드](https://github.com/kobongsoo/BERT/blob/master/sbert/cross-encoder/sbert-crossencoder-test3.ipynb),[테스트코드](https://github.com/kobongsoo/BERT/blob/master/sbert/cross-encoder/sbert-crossencoder-test.ipynb)
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+|모델     |korsts|klue-sts|glue(stsb)|stsb_multi_mt(en)|
+|:--------|------:|--------:|--------------:|------------:|
+|**albert-small-kor-cross-encoder-v1**    |0.8455    |0.8526    |0.8513           |0.7976|
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 ## Usage and Performance
 
 Pre-trained models can be used like this: