Update README.md

README.md

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----
-license: mit
----
-# Description
-Metal Ion Binding prediction is a binary classification task where each input protein *x* is mapped to a label *y* ∈ {0, 1}, corresponding to whether there are metal ion–binding sites in the protein.
-
-The digital label means:
-
-0: No 
-
-1: Yes
-
-# Splits
-
-**Structure type:** PDB
-
-The dataset is from [**Exploring evolution-aware & -free protein language models as protein function predictors**](https://arxiv.org/abs/2206.06583). We employ all proteins from the original dataset, and split them based on 70% structure similarity (see [ProteinShake](https://github.com/BorgwardtLab/proteinshake/tree/main)), with the number of training, validation and test set shown below:
-
-- Train: 5797
-- Valid: 719
-- Test:  719
-
-# Data format
-
-We organize all data in LMDB format. The architecture of the databse is like:
-
-**length:** The number of samples
-
-**0:** 
-
-- **name:** The PDB ID of the protein
-- **chain:** The chain ID of the protein
-- **seq:** The structure-aware sequence
-- **label:** Digital label of the sequence
-
-**1:**
-
-**···**
-
+---
+license: mit
+---
+# Description
+Metal Ion Binding prediction is a binary classification task where each input protein *x* is mapped to a label *y* ∈ {0, 1}, corresponding to whether there are metal ion–binding sites in the protein.
+
+
+
+# Splits
+
+**Structure type:** PDB
+
+The dataset is from [**Exploring evolution-aware & -free protein language models as protein function predictors**](https://arxiv.org/abs/2206.06583). We employ all proteins from the original dataset, and split them based on 70% structure similarity (see [ProteinShake](https://github.com/BorgwardtLab/proteinshake/tree/main)), with the number of training, validation and test set shown below:
+
+- Train: 5797
+- Valid: 719
+- Test:  719
+
+# Label
+
+0: No 
+
+1: Yes
+