vocab-transformers
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dense_encoder-msmarco-distilbert-word2vec256k-MLM_210k_emb_updated

Sentence Similarity

sentence-transformers

feature-extraction

text-embeddings-inference

Inference Endpoints

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nreimers commited on Feb 21, 2022

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@@ -11,9 +11,9 @@ tags:
 **Note: Token embeddings where updated!**
-This model is based on [vocab-transformers/msmarco-distilbert-word2vec256k-MLM_210k](https://huggingface.co/vocab-transformers/msmarco-distilbert-word2vec256k-MLM_210k) with a 256k sized vocabulary initialized with word2vec that has been trained with MLM for 210k steps with frozen embedding matrix on the MSMARCO corpus.
-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:

 **Note: Token embeddings where updated!**
+This model is based on [vocab-transformers/msmarco-distilbert-word2vec256k-MLM_210k](https://huggingface.co/vocab-transformers/msmarco-distilbert-word2vec256k-MLM_210k) with a 256k sized vocabulary initialized with word2vec that has been trained with MLM for 210k.
+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: