benchmark last stable version

research_files/bench.py

@@ -37,11 +37,11 @@ if __name__ == '__main__':
     )
 
     for model in [
-        # "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",  # Baseline Multilingual - sBERT
-        # 'hiiamsid/sentence_similarity_spanish_es',          # Spanish similarity - sBERT
-        # "jaimevera1107/all-MiniLM-L6-v2-similarity-es",     # Spanish similarity - sBERT
-        # "google-bert/bert-base-multilingual-cased",                     # mBERT (google)
-        # "sentence-transformers/LaBSE",                                  # LaBSE (google)
+        "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",  # Baseline Multilingual - sBERT
+        'hiiamsid/sentence_similarity_spanish_es',          # Spanish similarity - sBERT
+        "jaimevera1107/all-MiniLM-L6-v2-similarity-es",     # Spanish similarity - sBERT
+        "google-bert/bert-base-multilingual-cased",                     # mBERT (google)
+        "sentence-transformers/LaBSE",                                  # LaBSE (google)
         "FacebookAI/xlm-roberta-base"                                  # XLM-R (facebook)
     ]:
         print("Evaluating Model (3 methods):", model)
@@ -54,7 +54,6 @@ if __name__ == '__main__':
             device=torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
         ) for hyper, method in zip([4, 2, 0.3], ['pelt', 'binseg', 'csim'])]
 
-
 def print_results(directory: str):
     """
     Prints average segmentation metrics from JSON result files in a directory.