vocab-transformers
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dense_encoder-msmarco-bert-base-word2vec256k_emb_updated

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sentence-transformers

feature-extraction

text-embeddings-inference

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nreimers commited on Feb 21, 2022

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 # dense_encoder-msmarco-bert-base-word2vec256k
 This model is based on [msmarco-word2vec256000-bert-base-uncased](https://huggingface.co/nicoladecao/msmarco-word2vec256000-bert-base-uncased) with a 256k sized vocabulary initialized with word2vec.
-It has been trained on MS MARCO using [MarginMSELoss](https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_margin-mse.py) with a frozen embedding matrix. See the train_script.py in this repository.
 Performance:

 # dense_encoder-msmarco-bert-base-word2vec256k
+**Note: Token embeddings where updated!**
 This model is based on [msmarco-word2vec256000-bert-base-uncased](https://huggingface.co/nicoladecao/msmarco-word2vec256000-bert-base-uncased) with a 256k sized vocabulary initialized with word2vec.
+It has been trained on MS MARCO using [MarginMSELoss](https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/ms_marco/train_bi-encoder_margin-mse.py). See the train_script.py in this repository.
 Performance: