| 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) |
|
|
