Update readme with disclaimer (#316)

* updated readme

* typo

* update landing page

docs/index.md

@@ -88,9 +88,9 @@ For more details on the FM-backbones and instructions to replicate the results,
 
 ## Evaluation setup
 
-With the FM, *eva* computes embeddings for all WSI patches which are then used as input to train a downstream head consisting of a single linear layer in a supervised setup for each of the benchmark datasets.
+*Note that the current version of eva implements the task- & model-independent and fixed default set up following the standard evaluation protocol proposed by [1] and described in the table below. We selected this approach to prioritize reliable, robust and fair FM-evaluation while being in line with common literature. Additionally, with future versions we are planning to allow the use of cross-validation and hyper-parameter tuning to find the optimal setup to achieve best possible performance on the implemented downstream tasks.*
 
-To standardize evaluations, the default configurations *eva* uses are based on the evaluation protocol proposed by [1] and dataset/task specific characteristics. We use early stopping with a patience of 5% of the maximal number of epochs.
+With the FM as input, *eva* computes embeddings for all WSI patches which are then used as input to train a downstream head consisting of a single linear layer in a supervised setup for each of the benchmark datasets. We use early stopping with a patience of 5% of the maximal number of epochs.
 
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