Update README.md

README.md

@@ -61,8 +61,8 @@ print(scores)
 ## Evaluation
 ***
 
-We evaluated our model on 500 random queries from the mMARCO-fr train set (which were excluded from training). Each of these queries has at least one relevant and up to 200 irrelevant passages. Below, we compared the model performance with other cross-encoder models fine-tuned on the same dataset:
-|    | model                                                                                                                                                                                  |   r-precision |   mrr@10 |   recall@10 (↑) |   recall@20 |   recall@50 |   recall@100 |
+We evaluated our model on 500 random queries from the mMARCO-fr train set (which were excluded from training). Each of these queries has at least one relevant and up to 200 irrelevant passages. Below, we compare the model performance with other cross-encoder models fine-tuned on the same dataset. We report the R-precision (RP), mean reciprocal rank (MRR), and recall at various cut-offs (R@k).
+|    | model                                                                                                                                                                                  |            RP |   MRR@10 |    R@10 (↑) |        R@20 |        R@50 |        R@100 |
 |---:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------:|---------:|------------:|------------:|------------:|-------------:|
 |  1 | **crossencoder-camembert-base-mmarcoFR**                                                                                                                                               |         35.65 |    50.44 |       82.95 |       91.5  |       96.8  |        98.8  |
 |  2 | [crossencoder-mMiniLMv2-L12-H384-distilled-from-XLMR-Large-mmarcoFR](https://huggingface.co/antoinelouis/crossencoder-mMiniLMv2-L12-H384-distilled-from-XLMR-Large-mmarcoFR)           |         34.37 |    51.01 |       82.23 |       90.6  |       96.45 |        98.4  |