diff --git a/torchtext/datasets/yahooanswers.py b/torchtext/datasets/yahooanswers.py
index 7e95e2c6ca..70c3d8b807 100644
--- a/torchtext/datasets/yahooanswers.py
+++ b/torchtext/datasets/yahooanswers.py
@@ -33,22 +33,29 @@
 
 @_add_docstring_header(num_lines=NUM_LINES, num_classes=10)
 @_create_dataset_directory(dataset_name=DATASET_NAME)
-@_wrap_split_argument(('train', 'test'))
+@_wrap_split_argument(("train", "test"))
 def YahooAnswers(root: str, split: Union[Tuple[str], str]):
     if not is_module_available("torchdata"):
         raise ModuleNotFoundError("Package `torchdata` not found. Please install following instructions at `https://github.com/pytorch/data`")
 
     url_dp = IterableWrapper([URL])
 
-    cache_dp = url_dp.on_disk_cache(
+    cache_compressed_dp = url_dp.on_disk_cache(
         filepath_fn=lambda x: os.path.join(root, _PATH),
-        hash_dict={os.path.join(root, _PATH): MD5}, hash_type="md5"
+        hash_dict={os.path.join(root, _PATH): MD5},
+        hash_type="md5"
     )
-    cache_dp = GDriveReader(cache_dp).end_caching(mode="wb", same_filepath_fn=True)
-    cache_dp = FileOpener(cache_dp, mode="b")
+    cache_compressed_dp = GDriveReader(cache_compressed_dp).end_caching(mode="wb", same_filepath_fn=True)
+    cache_compressed_dp = FileOpener(cache_compressed_dp, mode="b")
 
-    extracted_files = cache_dp.read_from_tar()
+    cache_decompressed_dp = cache_compressed_dp.on_disk_cache(
+        filepath_fn=lambda x: os.path.join(root, _EXTRACTED_FILES[split])
+    )
+    cache_decompressed_dp = FileOpener(cache_decompressed_dp, mode="b")
+    cache_decompressed_dp = cache_decompressed_dp.read_from_tar()
+    cache_decompressed_dp = cache_decompressed_dp.filter(lambda x: _EXTRACTED_FILES[split] in x[0])
+    cache_decompressed_dp = cache_decompressed_dp.end_caching(mode="wb", same_filepath_fn=True)
 
-    filter_extracted_files = extracted_files.filter(lambda x: _EXTRACTED_FILES[split] in x[0])
+    data_dp = FileOpener(cache_decompressed_dp, mode="b")
 
-    return filter_extracted_files.parse_csv().map(fn=lambda t: (int(t[0]), " ".join(t[1:])))
+    return data_dp.parse_csv().map(fn=lambda t: (int(t[0]), " ".join(t[1:])))