update: name of metric to DetailedWER

README.md

@@ -1,5 +1,5 @@
 ---
-title: ArgWER
+title: DetailedWER
 tags:
 - evaluate
 - metric
@@ -12,17 +12,17 @@ app_file: app.py
 pinned: false
 ---
 
-# Metric Card for ArgWER
+# Metric Card for DetailedWER
 
 ## Metric Description
-ArgWER is an enhanced version of the Word Error Rate (WER) metric used for evaluating speech recognition systems. While it calculates the standard WER score, it also provides detailed information about different types of errors (insertions, deletions, and substitutions) when requested. This makes it particularly useful for detailed analysis of speech recognition system performance.
+DetailedWER is an enhanced version of the Word Error Rate (WER) metric used for evaluating speech recognition systems. While it calculates the standard WER score, it also provides detailed information about different types of errors (insertions, deletions, and substitutions) when requested. This makes it particularly useful for detailed analysis of speech recognition system performance.
 
 ## How to Use
 The metric can be loaded and used through the `evaluate` library:
 
 ```python
 import evaluate
-wer = evaluate.load("EduardoPacheco/argwer")
+wer = evaluate.load("argmaxinc/detailed-wer")
 predictions = ["this is the prediction", "there is an other sample"]
 references = ["this is the reference", "there is another one"]
 wer_score = wer.compute(predictions=predictions, references=references)
@@ -59,7 +59,7 @@ Basic usage:
 ```python
 predictions = ["this is the prediction", "there is an other sample"]
 references = ["this is the reference", "there is another one"]
-wer = evaluate.load("EduardoPacheco/argwer")
+wer = evaluate.load("argmaxinc/detailed-wer")
 
 # Basic WER score
 wer_score = wer.compute(predictions=predictions, references=references)

app.py

@@ -2,5 +2,5 @@ import evaluate
 from evaluate.utils import launch_gradio_widget
 
 
-module = evaluate.load("EduardoPacheco/argwer")
+module = evaluate.load("argmaxinc/detailed-wer")
 launch_gradio_widget(module)

argwer.py → detailed_wer.py

@@ -66,14 +66,14 @@ Examples:
 
     >>> predictions = ["this is the prediction", "there is an other sample"]
     >>> references = ["this is the reference", "there is another one"]
-    >>> wer = evaluate.load("EduardoPacheco/argwer")
+    >>> wer = evaluate.load("argmaxinc/detailed-wer")
     >>> wer_score = wer.compute(predictions=predictions, references=references)
     >>> print(wer_score)
     0.5
 """
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
-class ArgWER(evaluate.Metric):
+class DetailedWER(evaluate.Metric):
     """TODO: Short description of my evaluation module."""
 
     def _info(self):