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Dense Encoder - Distilbert - Frozen Token Embeddings

This model is a distilbert-base-uncased model trained for 30 epochs (235k steps), 64 batch size with MarginMSE Loss on MS MARCO dataset.

The token embeddings were frozen.

Dataset Model with updated token embeddings Model with frozen embeddings
TREC-DL 19 70.68 68.60
TREC-DL 20 67.69 70.21
FiQA 28.89 28.60
Robust04 39.56 39.08
TREC-COVID v2 69.80 69.84
TREC-NEWS 37.97 38.27
Avg. 4 BEIR tasks 44.06 43.95
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