readme: # 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 |
  
  