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# dense_encoder-msmarco-distilbert-word2vec256k-MLM_210k
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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.
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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.
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# dense_encoder-msmarco-distilbert-word2vec256k-MLM_210k
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**Note: Token embeddings where updated!**
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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.
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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.
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