update pandas indexing

app.py

@@ -11,7 +11,7 @@ description = """<p style='text-align: center'>
 As I introduce myself to the entirety of the 🤗 ecosystem, I've put together this Space to show off a temporary fix for a current 🪲 in the 🤗 Evaluate library. \n
 
 Check out the original, longstanding issue [here](https://github.com/huggingface/evaluate/issues/234). This details how it is currently impossible to \
-'evaluate.combine()' multiple metrics related to multilabel text classification. Particularly, one cannot 'combine()' the f1, precision, and recall scores for \
+`evaluate.combine()` multiple metrics related to multilabel text classification. Particularly, one cannot `combine` the `f1`, `precision`, and `recall` scores for \
 evaluation. I encountered this issue specifically while training [RoBERTa-base-DReiFT](https://huggingface.co/MarioBarbeque/RoBERTa-base-DReiFT) for multilabel \
 text classification of 805 labeled medical conditions based on drug reviews. \n
 
@@ -24,9 +24,9 @@ trained [multilabel text classification model](https://github.com/johngrahamreyn
 
 def evaluation(predictions, metrics) -> str: 
 
-    f1 = FixedF1(average=metrics["f1"])
-    precision = FixedPrecision(average=metrics["precision"])
-    recall = FixedRecall(average=metrics["recall"])
+    f1 = FixedF1(average=metrics.loc[metrics["Metric"] == "f1"]["Averaging Type"][0])
+    precision = FixedPrecision(average=metrics.loc[metrics["Metric"] == "precision"]["Averaging Type"][0])
+    recall = FixedRecall(average=metrics.loc[metrics["Metric"] == "recall"]["Averaging Type"][0])
     combined = evaluate.combine([f1, recall, precision])
 
     df = predictions.get_dataframe()