Update README.md

README.md

@@ -83,6 +83,8 @@ This released checkpoint uses multi-budget training with targets `[4, 8, 16, 32,
 
 ## Results
 
+All of the results can be found in [this space](https://huggingface.co/spaces/lightonai/hpool-regularization-results). The results are only on a subset of the 7 smaller BEIR datasets to make experiments easier and match AGC setup (SciFact, NFCorpus, ArguAna, TREC-Covid, FiQa, Touché, SciDocs). Given the original results of the hpool paper, we do not expect much different from running the whole BEIR suit.
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 ### Hierarchical Pooling Retention at 32 Tokens
 
 The table below reports retention at a 32-token document budget, measured against the full-token LateOn reference.