add microsoft harrier model result (270m, 596m variants)

model_results.json

@@ -1,4 +1,112 @@
 [
+    {
+        "model_name": "microsoft/harrier-oss-v1-270m",
+        "model_url": "https://huggingface.co/microsoft/harrier-oss-v1-270m",
+        "results": {
+            "mteb_avg": 0.6526,
+            "mteb_detailed": {
+                "FloresBitextMining_devtest": 0.1636,
+                "NTREXBitextMining_test": 0.939,
+                "Tatoeba_test": 0.9093,
+                "MassiveIntentClassification_test": 0.534,
+                "MassiveScenarioClassification_test": 0.5891,
+                "SIB200Classification_test": 0.7108,
+                "SIB200ClusteringS2S_test": 0.3309,
+                "ArmenianParaphrasePC_test": 0.9281,
+                "BelebeleRetrieval_test": 0.7683
+            },
+            "sts_spearman": 0.7092,
+            "sts_detailed": {
+                "Pearson_correlation": 0.6992,
+                "Spearman_correlation": 0.7092
+            },
+            "retrieval_top20": 0.7011,
+            "retrieval_detailed": {
+                "top1 within document": 0.4,
+                "top3 within document": 0.6,
+                "top5 within document": 0.74,
+                "top20 group mean macro": 0.8179,
+                "top20 all": 0.7011
+            },
+            "msmarco_top10": 0.724,
+            "msmarco_detailed": {
+                "reranking_mrr": 0.5237,
+                "retrieval_mrr": 0.3992,
+                "retrieval_top5_accuracy": 0.6003,
+                "retrieval_top10_accuracy": 0.724
+            },
+            "retrieval_translit_top20": 0.2011,
+            "retrieval_translit_detailed": {
+                "top1 within document": 0.19,
+                "top3 within document": 0.36,
+                "top5 within document": 0.44,
+                "top20 group mean macro": 0.4227,
+                "top20 all": 0.2011
+            },
+            "msmarco_translit_top10": 0.1719,
+            "msmarco_translit_detailed": {
+                "reranking_mrr": 0.367,
+                "retrieval_mrr": 0.0828,
+                "retrieval_top5_accuracy": 0.1267,
+                "retrieval_top10_accuracy": 0.1719
+            }
+        },
+        "model_size": "270M"
+    },
+    {
+        "model_name": "microsoft/harrier-oss-v1-0.6b",
+        "model_url": "https://huggingface.co/microsoft/harrier-oss-v1-0.6b",
+        "results": {
+            "mteb_avg": 0.6533,
+            "mteb_detailed": {
+                "FloresBitextMining_devtest": 0.2497,
+                "NTREXBitextMining_test": 0.9432,
+                "Tatoeba_test": 0.8939,
+                "MassiveIntentClassification_test": 0.5296,
+                "MassiveScenarioClassification_test": 0.5976,
+                "SIB200Classification_test": 0.6907,
+                "SIB200ClusteringS2S_test": 0.2729,
+                "ArmenianParaphrasePC_test": 0.9305,
+                "BelebeleRetrieval_test": 0.7711
+            },
+            "sts_spearman": 0.718,
+            "sts_detailed": {
+                "Pearson_correlation": 0.7053,
+                "Spearman_correlation": 0.718
+            },
+            "retrieval_top20": 0.6087,
+            "retrieval_detailed": {
+                "top1 within document": 0.38,
+                "top3 within document": 0.55,
+                "top5 within document": 0.7,
+                "top20 group mean macro": 0.7686,
+                "top20 all": 0.6087
+            },
+            "msmarco_top10": 0.7771,
+            "msmarco_detailed": {
+                "reranking_mrr": 0.5506,
+                "retrieval_mrr": 0.4395,
+                "retrieval_top5_accuracy": 0.6544,
+                "retrieval_top10_accuracy": 0.7771
+            },
+            "retrieval_translit_top20": 0.2283,
+            "retrieval_translit_detailed": {
+                "top1 within document": 0.16,
+                "top3 within document": 0.36,
+                "top5 within document": 0.49,
+                "top20 group mean macro": 0.4179,
+                "top20 all": 0.2283
+            },
+            "msmarco_translit_top10": 0.2612,
+            "msmarco_translit_detailed": {
+                "reranking_mrr": 0.4011,
+                "retrieval_mrr": 0.1312,
+                "retrieval_top5_accuracy": 0.1996,
+                "retrieval_top10_accuracy": 0.2612
+            }
+        },
+        "model_size": "596M"
+    },
     {
         "model_name": "Alibaba-NLP/gte-multilingual-base",
         "model_url": "https://huggingface.co/Alibaba-NLP/gte-multilingual-base",