Update README.md

README.md

@@ -337,7 +337,7 @@ multilabel:
 | Bleu-4        | 0.141         | 0.140       | 0.309              | **0.363**   |
 | SPICE         | 0.092         | 0.089       | 0.182              | **0.213**   |
 
-* We used the provided toolkit from the coco website to evaluate our data, but had to adjust the code to fit the 2017 data we used.
+* We used the provided toolkit from the coco website to evaluate our data, but had to adjust the code to fit the 2017-data-version we used.
 * For nearly all metrics (except to CIDEr) we have a difference of 0.1 to 0.2 - which is quite a margin but can be explained by
 considering that we used only ~7% of the training data for the LSTM.  
 * More reasons for our lower results: the cnn wasn't fully trained (precision was still low), no extended hyperparameter tuning for LSTM, no beam search implemented