Update README.md

README.md

@@ -21,7 +21,7 @@ This is a [ColBERTv1](https://github.com/stanford-futuredata/ColBERT) model: it
 
 To use this model, you will need to install the following libraries:
 ```
-pip install colbert-ir[faiss-gpu] faiss torch
+pip install colbert-ir @ git+https://github.com/stanford-futuredata/ColBERT.git faiss-gpu==1.7.2
 ```
 
 
@@ -67,7 +67,12 @@ with Run().context(RunConfig(nranks=n_gpu,experiment=experiment)):
 
 ## Evaluation
 
-*(tba)*
+We evaluated our model on the smaller development set of mMARCO-fr, which consists of 6,980 queries for a corpus of 8.8M candidate passages. Below, we compared the model performance with a biencoder model fine-tuned on the same dataset. We report the mean reciprocal rank (MRR) and recall at various cut-offs (R@k).
+
+| model                                                                                                                   | Vocab. | #Param. |  Size |   MRR@10 |   R@10 |   R@100(↑) |   R@500 |
+|:------------------------------------------------------------------------------------------------------------------------|:-------|--------:|------:|---------:|-------:|-----------:|--------:|
+| **colbertv1-camembert-base-mmarcoFR**                                                                                   |     🇫🇷 |    110M | 443MB |    29.51 |  54.21 |      80.00 |   88.40 |
+| [biencoder-camembert-base-mmarcoFR](https://huggingface.co/antoinelouis/biencoder-camembert-base-mmarcoFR)              |     🇫🇷 |    110M | 438MB |    28.53 |  51.46 |      77.82 |   89.13 |
 
 ## Training