| import json | |
| import os | |
| REPLACE_MAP = { | |
| "NDCG": "ndcg", | |
| "MAP": "map", | |
| "MRR": "mrr", | |
| "RECALL": "recall", | |
| "Recall": "recall", | |
| "P": "precision", | |
| } | |
| MODEL_TO_MODEL = { | |
| "bm25": "bm25", | |
| "bge": "bge-large-en-v1.5", | |
| "cohere": "Cohere-embed-english-v3.0", | |
| "e5": "e5-mistral-7b-instruct", | |
| "google": "google-gecko.text-embedding-preview-0409", | |
| "grit": "GritLM-7B", | |
| "inst-l": "instructor-large", | |
| "inst-xl": "instructor-xl", | |
| "openai": "text-embedding-3-large", | |
| "qwen2": "gte-Qwen2-7B-instruct", | |
| "qwen": "gte-Qwen1.5-7B-instruct", | |
| "sbert": "all-mpnet-base-v2", | |
| "sf": "SFR-Embedding-Mistral", | |
| "voyage": "voyage-large-2-instruct", | |
| } | |
| folders = os.listdir("bright_scores/main") + os.listdir("bright_scores/long_context") | |
| models = set( | |
| [ | |
| x.split("_")[-3] | |
| for x in folders | |
| if (os.path.isdir("bright_scores/main/" + x) or os.path.isdir("bright_scores/long_context/" + x)) | |
| ] | |
| ) | |
| print(models) | |
| for model in models: | |
| print(f"Converting {model}") | |
| result_template = { | |
| "dataset_revision": "a75a0eb483f6a5233a6efc2d63d71540a4443dfb", | |
| "evaluation_time": 0, | |
| "kg_co2_emissions": None, | |
| "mteb_version": "1.12.79", | |
| "scores": {"standard": [], "long": []}, | |
| "task_name": "BrightRetrieval", | |
| } | |
| for folder in [ | |
| x | |
| for x in folders | |
| if (os.path.isdir("bright_scores/main/" + x) or os.path.isdir("bright_scores/long_context/" + x)) | |
| and (x.split("_")[-3] == model) | |
| ]: | |
| if os.path.isdir("bright_scores/main/" + folder): | |
| results_path = os.path.join("bright_scores/main", folder, "results.json") | |
| split = "standard" | |
| else: | |
| results_path = os.path.join("bright_scores/long_context", folder, "results.json") | |
| assert "long_True" in folder, folder | |
| split = "long" | |
| with open(results_path) as f: | |
| results = json.load(f) | |
| if len(folder.split("_")) == 4: | |
| subset = folder.split("_")[0] | |
| elif len(folder.split("_")) == 5: | |
| subset = folder.split("_")[0] + "_" + folder.split("_")[1] | |
| result_template["scores"][split].append( | |
| { | |
| "hf_subset": subset, | |
| "languages": ["eng-Latn"], | |
| "main_score": results["NDCG@10"], | |
| **{"_at_".join([REPLACE_MAP.get(x, x) for x in k.split("@")]): v for k, v in results.items()}, | |
| } | |
| ) | |
| model_folder = MODEL_TO_MODEL[model] | |
| os.makedirs(f"results/{model_folder}/no_revision_available", exist_ok=True) | |
| print(f"Writing to: results/{model_folder}/no_revision_available/BrightRetrieval.json") | |
| with open(f"results/{model_folder}/no_revision_available/BrightRetrieval.json", "w") as f: | |
| json.dump(result_template, f, indent=4) | |