diff --git a/vdpwi/README.md b/vdpwi/README.md
index 5c11a57..bbf3dde 100644
--- a/vdpwi/README.md
+++ b/vdpwi/README.md
@@ -14,6 +14,10 @@ To run VDPWI on the SICK dataset, use the following command. If you have any pro
 ```
 python -m vdpwi vdpwi.sick.model.castor --dataset sick --lr 5e-4 --optimizer rmsprop --epochs 15 --batch-size 8 --rnn-hidden-dim 256 --epsilon 1e-7
 ```
+| Implementation and config |	Pearson'r  | Spearman's p | MSE
+| ------------- | ------------- | ------------- | ------------- |
+| Paper  | 0.8784  | 0.8199 | 0.2329|
+| PyTorch Implementation  | 0.8710 | 0.8092 | 0.2501
 
 ## MSRVID Dataset
 
@@ -27,10 +31,17 @@ python -m vdpwi vdpwi.msrvid.model.castor --dataset msrvid --batch-size 16 --epo
 To run VDPWI on (Raw) TrecQA, you first need to run `./get_trec_eval.sh` in `utils` under the repo root while inside the `utils` directory. This will download and compile the official `trec_eval` tool used for evaluation.
 
 Then, you can run:
+
 ```
-python -m vdpwi vdpwi.trecqa.model --dataset trecqa --epochs 5 --regularization 0.0005 --eps 0.1
+python -m vdpwi vdpwi.trecqa.model --dataset trecqa --epochs 5 --regularization 0.0005 --eps 0.1 --optimizer rmsprop --lr 0.0005 --batch-size 8 --rnn-hidden-dim 256
 ```
 
+
+| Implementation and config |	MAP  | MRR |
+| ------------- | ------------- | ------------- |
+| Paper  | 0.7588  |0.8219 
+| PyTorch Implementation | 0.7581 | 0.8172|
+
 The paper results are reported in [Noise-Contrastive Estimation for Answer Selection with Deep Neural Networks](https://dl.acm.org/citation.cfm?id=2983872).
 
 ## WikiQA Dataset
@@ -38,10 +49,16 @@ The paper results are reported in [Noise-Contrastive Estimation for Answer Selec
 You also need `trec_eval` for this dataset, similar to TrecQA.
 
 Then, you can run:
+
 ```
-python -m vdpwi vdpwi.wikiqa.model --epochs 10 --dataset wikiqa --batch-size 64 --lr 0.0004 --regularization 0.02
+python -m vdpwi vdpwi.wikiqa.model --dataset wikiqa --epochs 10 --batch-size 64 --lr 0.0005 --regularization 0.02 --optimizer rmsprop --rnn-hidden-dim 256
 ```
 
+| Implementation and config |	MAP  | MRR |
+| ------------- | ------------- | ------------- |
+| Paper  | 0.7090  |0.7234 
+| PyTorch Implementation | 0.7184 | 0.7286 |
+
 To see all options available, use
 ```
 python -m vdpwi --help