diff --git a/src/transformers/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py b/src/transformers/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py
index 77247495520c..8973c48c909f 100755
--- a/src/transformers/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py
+++ b/src/transformers/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py
@@ -113,7 +113,7 @@ def convert_fsmt_checkpoint_to_pytorch(fsmt_checkpoint_path, pytorch_dump_folder
         fsmt_folder_path, checkpoint_file, data_name_or_path, archive_map=models, **kwargs
     )
 
-    args = dict(vars(chkpt["args"]))
+    args = vars(chkpt["args"]["model"])
 
     src_lang = args["source_lang"]
     tgt_lang = args["target_lang"]
@@ -129,7 +129,7 @@ def convert_fsmt_checkpoint_to_pytorch(fsmt_checkpoint_path, pytorch_dump_folder
     src_vocab = rewrite_dict_keys(src_dict.indices)
     src_vocab_size = len(src_vocab)
     src_vocab_file = os.path.join(pytorch_dump_folder_path, "vocab-src.json")
-    print(f"Generating {src_vocab_file}")
+    print(f"Generating {src_vocab_file} of {src_vocab_size} of {src_lang} records")
     with open(src_vocab_file, "w", encoding="utf-8") as f:
         f.write(json.dumps(src_vocab, ensure_ascii=False, indent=json_indent))
 
@@ -137,13 +137,16 @@ def convert_fsmt_checkpoint_to_pytorch(fsmt_checkpoint_path, pytorch_dump_folder
     tgt_vocab = rewrite_dict_keys(tgt_dict.indices)
     tgt_vocab_size = len(tgt_vocab)
     tgt_vocab_file = os.path.join(pytorch_dump_folder_path, "vocab-tgt.json")
-    print(f"Generating {tgt_vocab_file}")
+    print(f"Generating {tgt_vocab_file} of {tgt_vocab_size} of {tgt_lang} records")
     with open(tgt_vocab_file, "w", encoding="utf-8") as f:
         f.write(json.dumps(tgt_vocab, ensure_ascii=False, indent=json_indent))
 
     # merges_file (bpecodes)
     merges_file = os.path.join(pytorch_dump_folder_path, VOCAB_FILES_NAMES["merges_file"])
-    fsmt_merges_file = os.path.join(fsmt_folder_path, "bpecodes")
+    for fn in ["bpecodes", "code"]:  # older fairseq called the merges file "code"
+        fsmt_merges_file = os.path.join(fsmt_folder_path, fn)
+        if os.path.exists(fsmt_merges_file):
+            break
     with open(fsmt_merges_file, encoding="utf-8") as fin:
         merges = fin.read()
     merges = re.sub(r" \d+$", "", merges, 0, re.M)  # remove frequency number
@@ -248,10 +251,6 @@ def convert_fsmt_checkpoint_to_pytorch(fsmt_checkpoint_path, pytorch_dump_folder
     print("\nLast step is to upload the files to s3")
     print(f"cd {data_root}")
     print(f"transformers-cli upload {model_dir}")
-    print(
-        "Note: CDN caches files for up to 24h, so either use a local model path "
-        "or use `from_pretrained(mname, use_cdn=False)` to use the non-cached version."
-    )
 
 
 if __name__ == "__main__":