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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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