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v1.0/experiments/audit/judge_swap_sensitivity.json

@@ -0,0 +1,60 @@
+{
+ "n_queries_old_judges": 250,
+ "weighted_prevalence_by_rule": {
+  "both2": {
+   "gemini_deepseek": 0.22130239980359695,
+   "claude_gpt": 0.29173019087951935
+  },
+  "min": {
+   "gemini_deepseek": 0.22130239980359695,
+   "claude_gpt": 0.29173019087951935
+  },
+  "either2": {
+   "gemini_deepseek": 0.44809181857239333,
+   "claude_gpt": 0.5739655066593017
+  }
+ },
+ "per_judge_calibration": {
+  "claude-haiku-5-5": {
+   "official_grade2": [
+    225,
+    300
+   ],
+   "random_grade0": [
+    600,
+    600
+   ]
+  },
+  "gpt-6-luna": {
+   "official_grade2": [
+    268,
+    300
+   ],
+   "random_grade0": [
+    600,
+    600
+   ]
+  },
+  "gemini-3.5-flash": {
+   "official_grade2": [
+    210,
+    250
+   ],
+   "random_grade0": [
+    500,
+    500
+   ]
+  },
+  "deepseek-v4-flash": {
+   "official_grade2": [
+    216,
+    250
+   ],
+   "random_grade0": [
+    500,
+    500
+   ]
+  }
+ },
+ "note": "Pre-registered final-audit judges (Gemini/DeepSeek Flash, commandcode provider) stopped after 250/300 queries (provider out of credit); final judges Claude Haiku 5.5 + GPT-6 Luna (D24). Prevalence = population-weighted share of the 250 queries with >=1 non-official grade-2 answer, without adjudication, under each aggregation rule."
+}

v1.0/experiments/audit/summary.json

@@ -66,21 +66,21 @@
  "mrr_official": {
   "bm25_text": 0.5931693121693121,
   "bm25tuned_text": 0.5994378306878307,
-  "me5-base_text": 0.5403253968253968,
-  "me5-large_text": 0.5138478835978837,
-  "bge-m3_text": 0.5578531746031746,
-  "me5-base-ft_text": 0.41935582010582007,
-  "rrf_text": 0.6331177248677249,
+  "me5-base_text": 0.5423015873015874,
+  "me5-large_text": 0.509063492063492,
+  "bge-m3_text": 0.5583677248677249,
+  "me5-base-ft_text": 0.41965211640211636,
+  "rrf_text": 0.628117724867725,
   "rerank_text": 0.5303875661375662
  },
  "mrr_augmented": {
   "bm25_text": 0.71444708994709,
   "bm25tuned_text": 0.7217711640211641,
-  "me5-base_text": 0.6639814814814814,
-  "me5-large_text": 0.6135939153439154,
-  "bge-m3_text": 0.6791494708994708,
-  "me5-base-ft_text": 0.4995436507936508,
-  "rrf_text": 0.7453597883597883,
+  "me5-base_text": 0.6694603174603174,
+  "me5-large_text": 0.6092724867724867,
+  "bge-m3_text": 0.6780674603174603,
+  "me5-base-ft_text": 0.4997103174603174,
+  "rrf_text": 0.7448082010582011,
   "rerank_text": 0.6647354497354497
  },
  "kendall_tau_b": 1.0,
@@ -99,14 +99,14 @@
   "rrf_text",
   "bm25tuned_text"
  ],
- "t": "2026-10-20T09:32:07+00:00",
+ "t": "2026-10-20T10:47:57+00:00",
  "judged_at_10": {
-  "bm25_text": 1.0,
+  "bm25_text": 0.9996666666666667,
   "bm25tuned_text": 0.9106666666666666,
-  "me5-base_text": 1.0,
-  "me5-large_text": 0.5696666666666667,
-  "bge-m3_text": 1.0,
-  "me5-base-ft_text": 0.306,
+  "me5-base_text": 0.973,
+  "me5-large_text": 0.5666666666666667,
+  "bge-m3_text": 0.9913333333333333,
+  "me5-base-ft_text": 0.30633333333333335,
   "rrf_text": 0.8823333333333333,
   "rerank_text": 1.0
  },
@@ -120,21 +120,21 @@
   "mrr_official": {
    "bm25_text": 0.5573996147345014,
    "bm25tuned_text": 0.5622977481612792,
-   "me5-base_text": 0.4953293537366722,
-   "me5-large_text": 0.45739948200083436,
-   "bge-m3_text": 0.5449550032869708,
-   "me5-base-ft_text": 0.39449676902121944,
-   "rrf_text": 0.6143545639626673,
+   "me5-base_text": 0.5001263059786162,
+   "me5-large_text": 0.4547558337653234,
+   "bge-m3_text": 0.5464715853419584,
+   "me5-base-ft_text": 0.3951252566586471,
+   "rrf_text": 0.6138232335079653,
    "rerank_text": 0.5137735042363784
   },
   "mrr_augmented": {
    "bm25_text": 0.6732859797530506,
    "bm25tuned_text": 0.6911709870268553,
-   "me5-base_text": 0.6138461920883039,
-   "me5-large_text": 0.541228558686142,
-   "bge-m3_text": 0.6564981822727697,
-   "me5-base-ft_text": 0.45196214194490303,
-   "rrf_text": 0.7181798246757222,
+   "me5-base_text": 0.6218179299533096,
+   "me5-large_text": 0.5390944416932401,
+   "bge-m3_text": 0.6560206659079153,
+   "me5-base-ft_text": 0.45190621811375575,
+   "rrf_text": 0.7285021068452951,
    "rerank_text": 0.6349257840215718
   },
   "strata_population": {
@@ -150,7 +150,7 @@
    "hit1_cite1": 75
   }
  },
- "kendall_tau_b_unweighted": 0.9285714285714286,
+ "kendall_tau_b_unweighted": 1.0,
  "bootstrap": "stratified (within-stratum resampling), population-weighted; n_boot=1000",
  "cited_by_official_reply_by_grade": {
   "0": {
@@ -208,7 +208,7 @@
   ],
   [
    "Judged@10: pooled runs (min) / held-out run(s)",
-   "1.00 / 0.91, 0.57, 0.31, 0.88"
+   "0.97 / 0.91, 0.57, 0.31, 0.88"
   ],
   [
    "Cited by the official reply: grade 2 / 1 / 0 (non-official)",

v1.0/experiments/audit_ext/audit/adjudication_meta.json

@@ -0,0 +1,15 @@
+{
+ "n": 947,
+ "status": {
+  "id": "jdgb-15ad868431be4e22",
+  "intent": "ParlIR audit adjudication",
+  "total": 947,
+  "done": 947,
+  "failed": 0,
+  "cost": 10.957932000000008,
+  "running": false,
+  "model": "anthropic/claude-opus-5-5",
+  "elapsedS": 89.8
+ },
+ "t": "2026-10-20T10:40:38+00:00"
+}

v1.0/experiments/audit_ext/audit/judge_errors.jsonl

@@ -0,0 +1,4 @@
+{"qid": "P-9-2024-001007", "family": "judge-gpt", "agent_id": "audit-judge-gpt-P-9-2024-001007-2", "t": "2026-10-20T10:11:14+00:00", "prompt_sha256": "7af5267e550683b863764b1bbe98d43104329473e36bf5d94ad1875eb720d6df", "error": "RuntimeError('[openai-codex/gpt-6-luna] Retry budget exhausted after 10 retries: Codex error event: Codex is at capacity, please try again later (code=turn_rate_limit_exceeded)')"}
+{"qid": "E-10-2024-001730", "family": "judge-gpt", "agent_id": "audit-judge-gpt-E-10-2024-001730-2", "t": "2026-10-20T10:19:16+00:00", "prompt_sha256": "39460d3d414c20c2f17c656edc140abd62978f5aead03a52d8626fa8f9996132", "error": "RuntimeError('[openai-codex/gpt-6-luna] Retry budget exhausted after 10 retries: Codex error event: Codex is at capacity, please try again later (code=turn_rate_limit_exceeded)')"}
+{"qid": "E-10-2024-002940", "family": "judge-gpt", "agent_id": "audit-judge-gpt-E-10-2024-002940-2", "t": "2026-10-20T10:21:13+00:00", "prompt_sha256": "6aff6e116a96e9d08203e17bd2d8708b0a3e25f2f542f318ca895389b315d074", "error": "RuntimeError('[openai-codex/gpt-6-luna] Retry budget exhausted after 10 retries: Codex error event: Codex is at capacity, please try again later (code=turn_rate_limit_exceeded)')"}
+{"qid": "E-10-2025-001445", "family": "judge-gpt", "agent_id": "audit-judge-gpt-E-10-2025-001445-2", "t": "2026-10-20T10:30:34+00:00", "prompt_sha256": "1193e66519dc5588f72664c1d2252654a73105ddf41857745f8e4e6c94b7a658", "error": "RuntimeError('[openai-codex/gpt-6-luna] Interrupted OpenAI Codex response after 256 consecutive whitespace-only tool-call argument delta events (768 chars, sequence 693..948) for item fc_0fc816be2053ac89016ad742c40bd881919b3668ed54f54a18.')"}

v1.0/experiments/audit_ext/audit/pools_meta.json

@@ -0,0 +1,21 @@
+{
+ "extends": "base audit pools (same 300 queries)",
+ "extra_runs": [
+  "me5-large_text",
+  "me5-base-ft_text",
+  "rrf_text",
+  "bm25tuned_text",
+  "me5-base-ftdm_text"
+ ],
+ "depth": 10,
+ "n_queries": 300,
+ "n_pairs": 5449,
+ "new_docs_by_run_with_overlap": {
+  "me5-large_text": 1291,
+  "me5-base-ft_text": 2082,
+  "bm25tuned_text": 268,
+  "me5-base-ftdm_text": 1927,
+  "rrf_text": 353
+ },
+ "t": "2026-10-20T10:02:04+00:00"
+}

v1.0/experiments/audit_full/audit/human_key.json

@@ -0,0 +1,2301 @@
+[
+ {
+  "row": 1,
+  "qid": "E-10-2025-001200",
+  "doc": "E-10-2025-001200-ASW",
+  "bucket": "official",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "control:official",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 2,
+  "qid": "E-10-2026-001997",
+  "doc": "E-10-2026-001997-ASW",
+  "bucket": "official",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "control:official",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 3,
+  "qid": "E-10-2024-002579",
+  "doc": "E-9-2020-001706-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bge-m3_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
+   "final": 1
+  }
+ },
+ {
+  "row": 4,
+  "qid": "E-10-2025-000152",
+  "doc": "E-8-2017-002571-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "me5-large_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 0,
+   "final": 0
+  }
+ },
+ {
+  "row": 5,
+  "qid": "E-10-2025-002129",
+  "doc": "E-10-2026-000840-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bm25_text",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 6,
+  "qid": "E-10-2025-001765",
+  "doc": "E-10-2025-001765-ASW",
+  "bucket": "official",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "control:official",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 7,
+  "qid": "E-10-2026-002224",
+  "doc": "E-9-2021-005548-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 8,
+  "qid": "E-9-2024-000237",
+  "doc": "E-10-2025-000507-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 0,
+   "final": 1
+  }
+ },
+ {
+  "row": 9,
+  "qid": "P-9-2024-001129",
+  "doc": "E-9-2020-000219-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bge-m3_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 2,
+   "final": 1
+  }
+ },
+ {
+  "row": 10,
+  "qid": "E-9-2024-000399",
+  "doc": "E-8-2015-010837-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "me5-base-ftdm_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 2,
+   "final": 1
+  }
+ },
+ {
+  "row": 11,
+  "qid": "E-10-2025-002203",
+  "doc": "E-10-2025-002203-ASW",
+  "bucket": "official",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "control:official",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 1,
+   "final": 1
+  }
+ },
+ {
+  "row": 12,
+  "qid": "E-10-2025-000141",
+  "doc": "E-9-2022-004065-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bm25_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 13,
+  "qid": "E-10-2026-002241",
+  "doc": "E-9-2023-001537-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 14,
+  "qid": "E-10-2024-003086",
+  "doc": "E-9-2019-003694-ASW",
+  "bucket": "random",
+  "sources": [
+   "control:random"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 0,
+   "final": 0
+  }
+ },
+ {
+  "row": 15,
+  "qid": "E-10-2026-002584",
+  "doc": "P-10-2024-002152-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "me5-base_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 16,
+  "qid": "E-10-2025-004499",
+  "doc": "E-9-2021-000810-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "me5-base_text"
+  ],
+  "grades": {
+   "judge-claude": 1,
+   "judge-gpt": 2,
+   "final": 1
+  }
+ },
+ {
+  "row": 17,
+  "qid": "E-9-2024-000649",
+  "doc": "E-10-2024-002466-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 18,
+  "qid": "E-10-2024-002941",
+  "doc": "E-9-2022-001436-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
+   "final": 1
+  }
+ },
+ {
+  "row": 19,
+  "qid": "E-10-2024-001988",
+  "doc": "P-10-2026-000095-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 20,
+  "qid": "E-10-2026-001923",
+  "doc": "E-10-2025-002157-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 21,
+  "qid": "E-10-2024-002450",
+  "doc": "E-9-2021-000718-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bge-m3_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
+   "final": 2
+  }
+ },
+ {
+  "row": 22,
+  "qid": "P-10-2026-003417",
+  "doc": "E-9-2022-001156-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 23,
+  "qid": "E-9-2024-000252",
+  "doc": "E-8-2015-007252-ASW",
+  "bucket": "random",
+  "sources": [
+   "control:random"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 0,
+   "final": 0
+  }
+ },
+ {
+  "row": 24,
+  "qid": "E-10-2025-003860",
+  "doc": "E-10-2025-000376-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 25,
+  "qid": "E-10-2025-000615",
+  "doc": "E-9-2021-005180-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 26,
+  "qid": "E-10-2025-000676",
+  "doc": "E-10-2025-001341-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
+   "final": 1
+  }
+ },
+ {
+  "row": 27,
+  "qid": "E-10-2025-003345",
+  "doc": "P-9-2023-002463-ASW",
+  "bucket": "both2_nonofficial",
+  "sources": [
+   "bge-m3_text",
+   "bm25_text",
+   "me5-base_text"
+  ],
+  "grades": {
+   "judge-claude": 2,
+   "judge-gpt": 2,
+   "final": 2
+  }
+ },
+ {
+  "row": 28,
+  "qid": "E-10-2025-005038",
+  "doc": "E-8-2015-015608-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bm25_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
+   "final": 1
+  }
+ },
+ {
+  "row": 29,
+  "qid": "E-10-2026-002960",
+  "doc": "E-8-2015-004592-ASW",
+  "bucket": "disagree",
+  "sources": [
+   "bm25_text",
+   "rerank_text"
+  ],
+  "grades": {
+   "judge-claude": 0,
+   "judge-gpt": 1,
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v1.0/experiments/audit_full/audit/human_key_meta.json

@@ -0,0 +1,24 @@
+{
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+}

v1.0/experiments/audit_full/audit/sample.json

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+ },
+ "t": "2026-10-20T08:08:52+00:00"
+}

v1.0/experiments/audit_full/audit/summary.json

@@ -0,0 +1,217 @@
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+  "me5-base-ft_text": 0.41965211640211636,
+  "rrf_text": 0.628117724867725,
+  "rerank_text": 0.5303875661375662
+ },
+ "mrr_augmented": {
+  "bm25_text": 0.71444708994709,
+  "bm25tuned_text": 0.7217711640211641,
+  "me5-base_text": 0.6694603174603174,
+  "me5-large_text": 0.6134986772486772,
+  "bge-m3_text": 0.6780674603174603,
+  "me5-base-ft_text": 0.5229325396825397,
+  "rrf_text": 0.7480820105820106,
+  "rerank_text": 0.6647354497354497
+ },
+ "kendall_tau_b": 1.0,
+ "kendall_tau_b_ci": [
+  0.6428571428571429,
+  1.0
+ ],
+ "pairwise_reversals": [],
+ "families": [
+  "judge-claude",
+  "judge-gpt"
+ ],
+ "held_out": [],
+ "t": "2026-10-20T10:48:10+00:00",
+ "judged_at_10": {
+  "bm25_text": 0.9996666666666667,
+  "bm25tuned_text": 0.9996666666666667,
+  "me5-base_text": 0.977,
+  "me5-large_text": 0.9776666666666667,
+  "bge-m3_text": 0.9933333333333333,
+  "me5-base-ft_text": 0.994,
+  "rrf_text": 1.0,
+  "rerank_text": 1.0
+ },
+ "weighted": {
+  "queries_with_nonofficial_grade2": 0.5384856777960255,
+  "queries_with_nonofficial_grade2_ci": [
+   0.46765067201849114,
+   0.6089387581341615
+  ],
+  "nonofficial_grade2_per_query_mean": 1.6586328528857335,
+  "mrr_official": {
+   "bm25_text": 0.5573996147345014,
+   "bm25tuned_text": 0.5622977481612792,
+   "me5-base_text": 0.5001263059786162,
+   "me5-large_text": 0.4547558337653234,
+   "bge-m3_text": 0.5464715853419584,
+   "me5-base-ft_text": 0.3951252566586471,
+   "rrf_text": 0.6138232335079653,
+   "rerank_text": 0.5137735042363784
+  },
+  "mrr_augmented": {
+   "bm25_text": 0.6732859797530506,
+   "bm25tuned_text": 0.6911709870268553,
+   "me5-base_text": 0.6218179299533096,
+   "me5-large_text": 0.5417354410474304,
+   "bge-m3_text": 0.6560206659079153,
+   "me5-base-ft_text": 0.4800962314257358,
+   "rrf_text": 0.729646558240157,
+   "rerank_text": 0.6349257840215718
+  },
+  "strata_population": {
+   "hit0_cite0": 5813,
+   "hit0_cite1": 250,
+   "hit1_cite0": 4749,
+   "hit1_cite1": 150
+  },
+  "strata_sampled": {
+   "hit0_cite0": 75,
+   "hit0_cite1": 75,
+   "hit1_cite0": 75,
+   "hit1_cite1": 75
+  }
+ },
+ "kendall_tau_b_unweighted": 1.0,
+ "bootstrap": "stratified (within-stratum resampling), population-weighted; n_boot=1000",
+ "cited_by_official_reply_by_grade": {
+  "0": {
+   "cited": 2,
+   "n": 8936,
+   "rate": 0.00022381378692927484
+  },
+  "1": {
+   "cited": 97,
+   "n": 3446,
+   "rate": 0.028148578061520605
+  },
+  "2": {
+   "cited": 74,
+   "n": 538,
+   "rate": 0.137546468401487
+  }
+ },
+ "table_rows": [
+  [
+   "Sampled test queries / judged pairs",
+   "300 / 13220"
+  ],
+  [
+   "Inter-judge Cohen's $\\kappa$ (3 grades)",
+   "0.603"
+  ],
+  [
+   "Official answers graded 2 (95\\% CI)",
+   "272/300 (87--93\\%)"
+  ],
+  [
+   "Random controls graded 0 (95\\% CI)",
+   "600/600 (99--100\\%)"
+  ],
+  [
+   "Queries with $\\geq$1 non-official grade-2 answer in the pool, sample",
+   "191/300 (58--69\\%)"
+  ],
+  [
+   "\\quad same, weighted to the test population (95\\% CI)",
+   "54\\% (47--61\\%)"
+  ],
+  [
+   "Non-official grade-2 / grade-1 answers per query (sample)",
+   "1.79 / 11.49"
+  ],
+  [
+   "Kendall's $\\tau_b$ of weighted orderings (95\\% CI)",
+   "1.000 (0.643--1.000)"
+  ],
+  [
+   "Pairwise system reversals",
+   "0 of 28"
+  ],
+  [
+   "Judged@10: pooled runs (min) / held-out run(s)",
+   "0.98 / "
+  ],
+  [
+   "Cited by the official reply: grade 2 / 1 / 0 (non-official)",
+   "14\\% / 3\\% / 0\\%"
+  ]
+ ]
+}

v1.0/experiments/audit_full/audit/summary_9systems.json

@@ -0,0 +1,223 @@
+{
+ "n_queries": 300,
+ "n_judged_pairs": 13220,
+ "kappa": 0.6028393739930185,
+ "confusion": {
+  "1-1": 2056,
+  "0-1": 1281,
+  "0-0": 8238,
+  "2-2": 516,
+  "1-2": 432,
+  "1-0": 493,
+  "0-2": 28,
+  "2-1": 169,
+  "2-0": 7
+ },
+ "official_grade2": [
+  272,
+  300,
+  [
+   0.8684138011961098,
+   0.9346362090723985
+  ]
+ ],
+ "official_grade_ge1": [
+  298,
+  300,
+  [
+   0.9760219257685385,
+   0.9981698899670288
+  ]
+ ],
+ "random_grade0": [
+  600,
+  600,
+  [
+   0.9936380666717896,
+   1.0000000000000002
+  ]
+ ],
+ "queries_with_nonofficial_grade2": [
+  191,
+  300,
+  [
+   0.5808305794961457,
+   0.68904688297114
+  ]
+ ],
+ "nonofficial_grade2_per_query_mean": 1.7933333333333332,
+ "nonofficial_grade1_per_query_mean": 11.486666666666666,
+ "pool_yield_grade2_by_source": {
+  "bge-m3_text": 257,
+  "bm25_text": 245,
+  "me5-base_text": 231,
+  "rerank_text": 262,
+  "me5-base-ftdm_text": 90,
+  "me5-large_text": 17,
+  "me5-base-ft_text": 62,
+  "rrf_text": 9
+ },
+ "systems": [
+  "bm25_text",
+  "bm25tuned_text",
+  "me5-base_text",
+  "me5-large_text",
+  "bge-m3_text",
+  "me5-base-ft_text",
+  "rrf_text",
+  "rerank_text",
+  "me5-base-ftdm_text"
+ ],
+ "mrr_official": {
+  "bm25_text": 0.5931693121693121,
+  "bm25tuned_text": 0.5994378306878307,
+  "me5-base_text": 0.5423015873015874,
+  "me5-large_text": 0.509063492063492,
+  "bge-m3_text": 0.5583677248677249,
+  "me5-base-ft_text": 0.41965211640211636,
+  "rrf_text": 0.628117724867725,
+  "rerank_text": 0.5303875661375662,
+  "me5-base-ftdm_text": 0.6559391534391537
+ },
+ "mrr_augmented": {
+  "bm25_text": 0.71444708994709,
+  "bm25tuned_text": 0.7217711640211641,
+  "me5-base_text": 0.6694603174603174,
+  "me5-large_text": 0.6134986772486772,
+  "bge-m3_text": 0.6780674603174603,
+  "me5-base-ft_text": 0.5229325396825397,
+  "rrf_text": 0.7480820105820106,
+  "rerank_text": 0.6647354497354497,
+  "me5-base-ftdm_text": 0.7461666666666669
+ },
+ "kendall_tau_b": 1.0,
+ "kendall_tau_b_ci": [
+  0.6666666666666666,
+  1.0
+ ],
+ "pairwise_reversals": [],
+ "families": [
+  "judge-claude",
+  "judge-gpt"
+ ],
+ "held_out": [],
+ "t": "2026-10-20T10:48:04+00:00",
+ "judged_at_10": {
+  "bm25_text": 0.9996666666666667,
+  "bm25tuned_text": 0.9996666666666667,
+  "me5-base_text": 0.977,
+  "me5-large_text": 0.9776666666666667,
+  "bge-m3_text": 0.9933333333333333,
+  "me5-base-ft_text": 0.994,
+  "rrf_text": 1.0,
+  "rerank_text": 1.0,
+  "me5-base-ftdm_text": 0.9963333333333333
+ },
+ "weighted": {
+  "queries_with_nonofficial_grade2": 0.5384856777960255,
+  "queries_with_nonofficial_grade2_ci": [
+   0.46765067201849114,
+   0.6089387581341615
+  ],
+  "nonofficial_grade2_per_query_mean": 1.6586328528857335,
+  "mrr_official": {
+   "bm25_text": 0.5573996147345014,
+   "bm25tuned_text": 0.5622977481612792,
+   "me5-base_text": 0.5001263059786162,
+   "me5-large_text": 0.4547558337653234,
+   "bge-m3_text": 0.5464715853419584,
+   "me5-base-ft_text": 0.3951252566586471,
+   "rrf_text": 0.6138232335079653,
+   "rerank_text": 0.5137735042363784,
+   "me5-base-ftdm_text": 0.6117512933085847
+  },
+  "mrr_augmented": {
+   "bm25_text": 0.6732859797530506,
+   "bm25tuned_text": 0.6911709870268553,
+   "me5-base_text": 0.6218179299533096,
+   "me5-large_text": 0.5417354410474304,
+   "bge-m3_text": 0.6560206659079153,
+   "me5-base-ft_text": 0.4800962314257358,
+   "rrf_text": 0.729646558240157,
+   "rerank_text": 0.6349257840215718,
+   "me5-base-ftdm_text": 0.7046012183502631
+  },
+  "strata_population": {
+   "hit0_cite0": 5813,
+   "hit0_cite1": 250,
+   "hit1_cite0": 4749,
+   "hit1_cite1": 150
+  },
+  "strata_sampled": {
+   "hit0_cite0": 75,
+   "hit0_cite1": 75,
+   "hit1_cite0": 75,
+   "hit1_cite1": 75
+  }
+ },
+ "kendall_tau_b_unweighted": 0.9444444444444444,
+ "bootstrap": "stratified (within-stratum resampling), population-weighted; n_boot=1000",
+ "cited_by_official_reply_by_grade": {
+  "0": {
+   "cited": 2,
+   "n": 8936,
+   "rate": 0.00022381378692927484
+  },
+  "1": {
+   "cited": 97,
+   "n": 3446,
+   "rate": 0.028148578061520605
+  },
+  "2": {
+   "cited": 74,
+   "n": 538,
+   "rate": 0.137546468401487
+  }
+ },
+ "table_rows": [
+  [
+   "Sampled test queries / judged pairs",
+   "300 / 13220"
+  ],
+  [
+   "Inter-judge Cohen's $\\kappa$ (3 grades)",
+   "0.603"
+  ],
+  [
+   "Official answers graded 2 (95\\% CI)",
+   "272/300 (87--93\\%)"
+  ],
+  [
+   "Random controls graded 0 (95\\% CI)",
+   "600/600 (99--100\\%)"
+  ],
+  [
+   "Queries with $\\geq$1 non-official grade-2 answer in the pool, sample",
+   "191/300 (58--69\\%)"
+  ],
+  [
+   "\\quad same, weighted to the test population (95\\% CI)",
+   "54\\% (47--61\\%)"
+  ],
+  [
+   "Non-official grade-2 / grade-1 answers per query (sample)",
+   "1.79 / 11.49"
+  ],
+  [
+   "Kendall's $\\tau_b$ of weighted orderings (95\\% CI)",
+   "1.000 (0.667--1.000)"
+  ],
+  [
+   "Pairwise system reversals",
+   "0 of 36"
+  ],
+  [
+   "Judged@10: pooled runs (min) / held-out run(s)",
+   "0.98 / "
+  ],
+  [
+   "Cited by the official reply: grade 2 / 1 / 0 (non-official)",
+   "14\\% / 3\\% / 0\\%"
+  ]
+ ]
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/1_Pooling/config.json

@@ -0,0 +1,5 @@
+{
+    "embedding_dimension": 768,
+    "pooling_mode": "mean",
+    "include_prompt": true
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/2_Normalize/config.json

@@ -0,0 +1,4 @@
+{
+    "module_input_name": "sentence_embedding",
+    "module_output_name": "sentence_embedding"
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/README.md

@@ -0,0 +1,549 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:16873
+- loss:CachedMultipleNegativesRankingLoss
+- loss:MultipleNegativesRankingLoss
+base_model: intfloat/multilingual-e5-base
+widget:
+- source_sentence: 'query: Referendum in Hungary
+
+    Hungary has announced that it is holding a referendum on the compulsory quotas
+    for the number of migrants that the country is to receive from various refugee
+    camps in Europe. The question put in the referendum mentions the possibility of
+    the European Union deciding to relocate non-Hungarian citizens in Hungary without
+    the approval of the Hungarian Parliament.
+
+    What is the Commission’s position on this referendum, bearing in mind the need
+    to counter a possible domino effect among the Member States?'
+  sentences:
+  - 'passage: The discussions between the Commission and the Irish government on the
+    Irish rural development programme 2014-2020 are still ongoing, although nearing
+    completion. The Commission services are making every effort to resolve the outstanding
+    issues in order to allow Ireland to go ahead with the implementation of its rural
+    development programme as soon as possible. The Commission is not in a position
+    to provide details of the ongoing discussions.'
+  - 'passage: The Commission refers the Honourable Member to its answers to written
+    questions [REF][1] and [REF][2].
+
+    [1] http://www.europarl.europa.eu/sides/getAllAnswers.do?reference=E-2016-005414&language=EN
+
+    [2] http://www.europarl.europa.eu/sides/getAllAnswers.do?reference=P-2016-005587&language=EN'
+  - 'passage: It is the Commission''s understanding that the Hungarian referendum
+    relates to future decisions to be taken.
+
+    The decision making process agreed to by all EU Member States, as enshrined in
+    the Treaties, will not be affected.
+
+    Neither the referendum called by the Hungarian Government nor its outcome affects
+    Hungary''s obligations under the EU Treaties.
+
+    The Treaty on European Union and the Treaty on the Functioning of the European
+    Union provide for measures in case a Member State does not comply with its obligations
+    under EU law.'
+- source_sentence: 'query: PCE/PEC - Written questions to the President of the European
+    Council
+
+    Does the President of the European Council intend to follow the same practice
+    as President Van Rompuy in replying to written parliamentary questions concerning
+    his own political activities?'
+  sentences:
+  - 'passage: In line with the President of the European Council''s willingness to
+    answer parliamentary questions in so far as they concern his own political activities,
+    the following reply is given to the Honourable Member:
+
+    In his speech at the event marking the 40th anniversary of the European People''s
+    Party, President Tusk said: ''I want to make an important declaration: I am terribly
+    proud to be in the same party with such people as Joseph Daul and Angela Merkel,
+    as Viktor Orbán and Manfred Weber, as Jean-Claude Juncker and Boyko Borissov.''
+
+    With this statement, President Tusk emphasised the positive meaning of the existence
+    within the EPP of diverse attitudes and different sensitivities, represented by
+    various leaders, and which constitutes good ground for shaping compromises and
+    a common strategy in order to respond to current challenges.'
+  - 'passage: The President of the European Council, Donald Tusk, intends to follow
+    the same practice as the former President of the European Council, Herman Van
+    Rompuy, and will therefore reply to parliamentary questions for written answer
+    only in so far as they concern his own political activities.'
+  - 'passage: The examination by the Commission of the reply sent by the Belgian authorities
+    regarding the long term operation of the Doel 1 and Doel 2 nuclear power plant
+    is still ongoing. The Commission cannot at this time prejudge the timing or the
+    outcome of this assessment.
+
+    If the ongoing assessment leads to the conclusion that the agreement between the
+    Belgian government and Electrabel involves State aid, the Commission would have
+    to assess the compatibility of this aid with the Treaty on the Functioning of
+    the European Union (TFEU). If the Commission has serious doubts about the compatibility
+    of the measure, it would open a formal investigation inviting third parties to
+    express their views.'
+- source_sentence: 'query: Sale of loan portfolio by HSH Nordbank to Hamburg and Schleswig-Holstein
+
+    Hamburg and Schleswig-Holstein are planning to purchase from HSH Nordbank a portfolio
+    of non-performing loans with a book value of EUR 6.2 billion.
+
+    What purchase price is being negotiated by the two states with the Commission
+    and what does the Commission consider to be the market price?
+
+    It is true that the states are proposing a markdown of around 40%, that is to
+    say around EUR 2.5 billion?'
+  sentences:
+  - 'passage: Commission officials met the UK Electoral Commission on 28 January 2015
+    to discuss the way referendums are organised in the UK.
+
+    The Commission will not register as a campaigning organisation under the terms
+    of the European Union Referendum Act 2015. As the Commission previously stated,
+    it will not campaign in the forthcoming referendum in the UK on EU membership
+    and will not provide funding for use in the referendum campaign. The Commission
+    will continue to exercise the tasks conferred on it by the Treaty, including the
+    provision of information.'
+  - 'passage: The Commission is aware of the fact that HSH Nordbank has restructured
+    the ship financing loans of a large borrower.
+
+    In general, aided banks, as part of their commercial credit policy, are entitled
+    to restructure non-performing loans in an attempt to reduce the corresponding
+    risks and to recover as much value as possible under the given circumstances.'
+  - 'passage: According to the October 2015 agreement in principle between the Commission
+    and the Ministerpräsidenten of Hamburg and Schleswig-Holstein, HSH Nordbank can
+    sell up to EUR 6.2 billion of assets (Exposure at Default) to the two Länder.
+    In order to ensure that the transfer does not entail aid to the bank, the sale
+    of assets must take place at market values.
+
+    The Commission''s independent valuation experts have undertaken the determination
+    of the market value for the relevant assets for the final decision on HSH Nordbank
+    adopted on 2 May 2016. Before the publication of the non-confidential version
+    of the decision, the Commission is not in a position to provide those values.'
+- source_sentence: 'query: How is the European Food Safety Authority striving to be
+    representative of the citizens of Europe?
+
+    Previously, the Commission has stated that it ‘strives to be representative of
+    the increasingly diverse European citizens it serves’ (response to Written Questions
+    [REF], [REF] and [REF]).
+
+    Does the Commission’s view mirror that of the European Food Safety Authority (EFSA)?
+
+    Could the EFSA provide 10 examples of its efforts to be representative of EU citizens
+    in practice?'
+  sentences:
+  - 'passage: With regard to the appraisal by the Spanish Authorities of their infrastructural
+    projects (including high-speed lines) the Commission has recalled, in the "Commission
+    Recommendation for a COUNCIL RECOMMENDATION on the 2015 National Reform Programme
+    of Spain and delivering a Council opinion on the 2015 Stability Programme of Spain",
+    that Spain has not made operational, yet, a system for conducting independent
+    assessments of major future infrastructure projects[1]. The Commission thereby
+    continues to reinforce its request to the Spanish authorities, in line with its
+    earlier outcome and recommendations.
+
+    [1] Point (9) : http://ec.europa.eu/europe2020/pdf/csr2015/csr2015_spain_en.pdf'
+  - 'passage: The Commission has referred the questions on how the European Food Safety
+    Authority (EFSA) strives to ensure that its workforce is representative of European
+    citizens to the EFSA, as the Authority is an independent EU agency with responsibility
+    for its staff matters. The response will be communicated directly to the Honourable
+    Member as soon as possible.'
+  - 'passage: As a follow-up to its recent response to written questions [REF] and
+    [REF][1] on how the European Food Safety Authority (EFSA) strives to ensure that
+    its workforce is representative of European citizens, the Commission has provided
+    to the Honourable Member on behalf of the EFSA, an extensive list of activities
+    EFSA is undertaking to ensure that its workforce is representative of the European
+    Union citizens.
+
+    To respond to the present question, the Commission has asked EFSA to provide 10
+    examples of its efforts to be representative of EU citizens in practice. The response
+    will be communicated directly to the Honourable Member as soon as possible.
+
+    [1] http://www.europarl.europa.eu/plenary/en/parliamentary-questions.html'
+- source_sentence: 'query: Milk quota
+
+    With the end of the milk quota system on 31 March 2015, what instruments have
+    been put in place to ensure continued support for the dairy sector in the EU?'
+  sentences:
+  - 'passage: As the Honourable Member may be aware, the Commission addressed a letter
+    of formal notice, under Article 258 of the Treaty on the functioning of the EU,
+    to Germany on 20 May 2015 concerning the application of the German Minimum Wage
+    Act to the transport sector. The German authorities replied in July maintaining
+    their position and in the same time expressing their readiness to hold talks with
+    the Commission as to the substance of the infringement case.
+
+    If no satisfactory solution can be reached with the German authorities, the Commission
+    would be entitled to proceed with the next formal step of the infringement procedure.'
+  - 'passage: The Honourable Member is kindly referred to the answer to written question
+    [REF][1].
+
+    [1] http://www.europarl.europa.eu/plenary/en/parliamentary-questions.html'
+  - 'passage: In the framework of the reform of the Common Agricultural Policy (CAP)
+    in 2013, no proposals were made to grant any compensation to dairy farmers because
+    of the end of the milk quota system, neither by the Commission, nor by the Council
+    or by the European Parliament. The Commission will not be making any such proposals
+    now.
+
+    It is important to recall that dairy farmers continue to receive direct income
+    support as part the comprehensive market oriented reform of the dairy sector that
+    started in 2003 and of which the end of dairy quota in 2015 was an integral part.
+
+    The CAP provides for a comprehensive toolkit to support the milk sector after
+    milk quota expiry. In addition to direct payments and rural development programmes,
+    safety net measures are available (intervention buying-in and private storage
+    aid), coupled with a regulatory framework for the Commission to react to exceptional
+    circumstances. In addition, to better monitor the milk market and anticipate disturbances
+    in its functioning when milk quotas are removed, a Milk Market Observatory has
+    been set up. The Common Market Organisation also provides for mechanisms to strengthen
+    relations between farmers and processors of milk, so that market signals are better
+    conveyed.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on intfloat/multilingual-e5-base
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base). It maps inputs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) <!-- at revision d128750597153bb5987e10b1c3493a34e5a4502a -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Supported Modality:** Text
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'XLMRobertaModel'})
+  (1): Pooling({'embedding_dimension': 768, 'pooling_mode': 'mean', 'include_prompt': True})
+  (2): Normalize({'module_input_name': 'sentence_embedding', 'module_output_name': 'sentence_embedding'})
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'query: Milk quota\nWith the end of the milk quota system on 31 March 2015, what instruments have been put in place to ensure continued support for the dairy sector in the EU?',
+    'passage: The Honourable Member is kindly referred to the answer to written question [REF][1].\n[1] http://www.europarl.europa.eu/plenary/en/parliamentary-questions.html',
+    'passage: In the framework of the reform of the Common Agricultural Policy (CAP) in 2013, no proposals were made to grant any compensation to dairy farmers because of the end of the milk quota system, neither by the Commission, nor by the Council or by the European Parliament. The Commission will not be making any such proposals now.\nIt is important to recall that dairy farmers continue to receive direct income support as part the comprehensive market oriented reform of the dairy sector that started in 2003 and of which the end of dairy quota in 2015 was an integral part.\nThe CAP provides for a comprehensive toolkit to support the milk sector after milk quota expiry. In addition to direct payments and rural development programmes, safety net measures are available (intervention buying-in and private storage aid), coupled with a regulatory framework for the Commission to react to exceptional circumstances. In addition, to better monitor the milk market and anticipate disturbances in its functioning when milk quotas are removed, a Milk Market Observatory has been set up. The Common Market Organisation also provides for mechanisms to strengthen relations between farmers and processors of milk, so that market signals are better conveyed.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities)
+# tensor([[ 1.0000,  0.3960,  0.4978],
+#         [ 0.3960,  1.0000, -0.0699],
+#         [ 0.4978, -0.0699,  1.0000]])
+```
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 16,873 training samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 100 samples:
+  |          | anchor                                                                               | positive                                                                             | negative                                                                              |
+  |:---------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------|
+  | type     | string                                                                               | string                                                                               | string                                                                                |
+  | modality | text                                                                                 | text                                                                                 | text                                                                                  |
+  | details  | <ul><li>min: 39 tokens</li><li>mean: 212.35 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 48 tokens</li><li>mean: 318.62 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 155 tokens</li><li>mean: 421.17 tokens</li><li>max: 512 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
+  |:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>query: No to excessive taxation imposed by EU governments on the working classes<br>The first set of conditions imposed under the third memorandum is the continued heavy taxation of working class households that has already been going on for years, a pill made all the more bitter by the preferential treatment accorded to big business interests in the form of exemption from municipal taxes and the non-imposition of fines for falsified invoices and tax returns.<br>In particular, the extortionate special property tax is becoming more firmly established and more widely imposed. Taxes on a wide range of basic consumer items such as such as wine and veal are also increasing, as well as the amount of road tax and the number of those paying it.<br>At the same time, the tax offensive is to be stepped up by the introduction of a new legal arsenal ostensibly imposing penalties on tax evasion. These include not only denial of facilities for repayment of arrears but also imprisonment and seizure of property...</code> | <code>passage: The Commission, as a partner in the negotiations has paid particular attention to the social fairness of the new European Stability Mechanism (ESM) programme to ensure that the adjustment is spread equitably and to protect the most vulnerable in society. The Commission has published its assessment of the ESM programme's social impact which concludes that, if implemented fully and timely, the measures foreseen in the programme will help Greece return to stability and growth in a financially and socially sustainable way, and will contribute to meet the most pressing social needs and challenges in Greece[1].<br>Disbursements by the ESM are made on the basis of compliance with respect to the conditions agreed in the Memorandum of Understanding (MoU), signed by Greece and the Commission, on behalf of the ESM. According to the commitments in the MoU, Greece will target a medium-term primary surplus to be achieved through a combination of upfront parametric fiscal reforms supported by a...</code>    | <code>passage: The Commission has made the work for fair and effective taxation a top priority over the past few years, to ensure that all companies pay tax where they generate their profits. Major new legislation[1] has been agreed so that all Member States implement common anti abuse rules and automatically exchange a wide range of information to fight corporate tax avoidance. In addition, the Digital Tax Package[2], adopted by the Commission in March 2018, aims to ensure that Member States can effectively tax digital companies, as well as more traditional businesses. A number of State aid cases have also been conducted, to prevent Member States from providing preferential tax treatment to certain companies.<br>Within the EU, Member States’ tax regimes are scrutinised under the Code of Conduct on Business Taxation, and those that are found to be harmful must be eliminated. Other aspects of Member States’ tax systems - such as Patent Boxes - have also been examined under the Code, to ensure th...</code>    |
+  | <code>query: Payment of the new Belgium road toll for haulage contractors<br>On 1 April 2016 the Belgian authorities will introduce a new road toll for lorries over 3.5 tonnes in weight that can only be paid if the vehicles concerned are fitted with a satellite controlled device. This new Eurovignette system only accepts payment through a specific ‘on board unit’ (OBU) even though the vehicles concerned may only occasionally be driven on Belgian roads. Before fitting this device in their lorries users must pay a deposit of EUR 135 to the contractor Satellic, a subsidiary of Deutsche Telekom, which will have the monopoly on operating this toll collection and verification system. Just the purchase and assembly of this OBU in the approximately 700 000 vehicles concerned will bring in EUR 95 million in revenue. As this payment system is not interoperable with other OBUs already fitted in haulage vehicles, hauliers are forced to fit this one.<br>1. Does the Commission know the details of how this servi...</code>    | <code>passage: 1. The service was awarded in a competitive tender. The details of the award of the contract are presented in the "News" section of the website of Viapass (http://www.viapass.be/en/news).<br>2. The Belgian tolling scheme will not be the first one where vehicles must be equipped with an ‘on board unit’ (OBU) to use tolled roads - the same requirement exists already in Poland, the Czech Republic and Austria. It has not had any significant impact on the free movement of people and goods in the Member States concerned, and is therefore unlikely to have such impacts in Belgium.<br>To the Commission's knowledge, there is no risk that only Satellic's OBUs can be used for paying tolls in Belgium. It would appear on the contrary that several third party providers are negotiating with Viapass the possibility to offer their services in Belgium. Axxès, which is one of them, already announces that it will be possible to use its on board unit to pay tolls in Belgium (https://www.axxes.fr/fr/taxe-...</code> | <code>passage: Portugal has opted for a distance based charging system for cars, light-duty vehicles and heavy goods vehicles. It has introduced also an electronic tolling system, although, on most motorways manual payment remains possible. Unlike the time-based charging (vignettes) still present in some other EU Members States, this type of road charging represents in the view of the Commission the right basis for ensuring that principles of proportionality and non-discrimination are respected.<br>Without prejudice of the specific rights and obligations of European Electronic Toll Service (EETS) providers and users pursuant to Directive 2019/520/EU, if the provider of the toll system can be qualified as a trader under EU consumer law[1], the provider is obliged to provide clear and comprehensible information before the payment is made, for instance on the main characteristics of the service, the total price and the arrangements for payment and performance. If the trader uses unfair contract te...</code>    |
+  | <code>query: Follow-up to questions [REF] on state aid cases involving airports, [REF] on reservoir management and [REF] on Directive 2000/60/EC<br>1. In its answer of 21 September 2015 to question [REF], the Commission states that it ‘is dealing with a number of pending cases concerning state aid for airports and intends to complete its investigations as quickly as possible’. Can the Commission provide a list of the cases currently open and an update on the situation with regard to state aid investigations involving airports?<br>2. In its answer to question [REF], the Commission states that ‘Spain must establish flood risk management plans by December 2015, which should include appropriate measures to reduce the risk from floods’. Can the Commission say whether Spain has now established and notified these plans?<br>3. In his answer to question [REF], Mr Vella states that ‘the Commission will assess the content of the final RBMPs submitted by the Spanish authorities and will take the necessary measur...</code> | <code>passage: 1. The Commission's currently open state aid investigations involving possible State aid to airports are listed in the attached document.<br>The Commission in general is unable to comment on ongoing investigations.<br>2. The Spanish authorities have communicated that the Flood Risk Management Plans according to the Floods Directive 2007/60/EC[1] have been adopted on 15 January 2016[2] for a number of river basin districts. The Directive requires Member States to report the plans by 22 March 2016. Plans are still missing for the river basin districts of Baleares, Catalonia and Canary Islands.<br>3. According to the Water Framework Directive 2000/60/EC[3] Member States are required to report the River Basin Management Plans to the Commission by 22 March 2016. The Commission will decide on any follow-up measure once it has assessed the contents of the plans.<br>[1] OJ L 288, 6.11.2007, p. 27<br>[2] Royal Decrees 18/2016, 19/2016, 20/2016 and 21/2016<br>[3] OJ L 327, 22.12.2000, p. 1</code>       | <code>passage: On the basis of the available information the Commission is not in a position to identify the reasons for the alleged miscalculation of the water level during the flood event.<br>Under the Floods Directive[1], Spain must establish flood risk management plans by December 2015, which should include appropriate measures to reduce the risk from floods according to local and regional circumstances. The choice and prioritisation of these measures is for Member States to decide provided that flood risk reduction in one area is not achieved at the expense of another in the same river basin and that EU legislation is respected.<br>EU legislation requires Member States to take an integrated approach for the management of the river basin and to ensure that no deterioration of the status of a water body takes place unless the conditions of Art. 4(7) of the Water Framework Directive[2] are fulfilled. In choosing measures, priority should be given to natural water retention measures[3], such as r...</code> |
+* Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim",
+      "mini_batch_size": 8,
+      "mini_batch_num_tokens": null,
+      "gather_across_devices": false,
+      "directions": [
+          "query_to_doc"
+      ],
+      "partition_mode": "joint",
+      "hardness_mode": null,
+      "hardness_strength": 0.0
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `learning_rate`: 2e-05
+- `warmup_steps`: 0.1
+- `fp16`: True
+- `seed`: 13
+- `dataloader_num_workers`: 2
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `learning_rate`: 2e-05
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: None
+- `warmup_steps`: 0.1
+- `optim`: adamw_torch_fused
+- `optim_args`: None
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `optim_target_modules`: None
+- `gradient_accumulation_steps`: 1
+- `average_tokens_across_devices`: True
+- `max_grad_norm`: 1.0
+- `label_smoothing_factor`: 0.0
+- `bf16`: False
+- `fp16`: True
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `use_cache`: False
+- `neftune_noise_alpha`: None
+- `torch_empty_cache_steps`: None
+- `auto_find_batch_size`: False
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `include_num_input_tokens_seen`: no
+- `log_level`: passive
+- `log_level_replica`: warning
+- `disable_tqdm`: False
+- `project`: huggingface
+- `trackio_space_id`: None
+- `trackio_bucket_id`: None
+- `trackio_static_space_id`: None
+- `per_device_eval_batch_size`: 8
+- `prediction_loss_only`: True
+- `eval_on_start`: False
+- `eval_do_concat_batches`: True
+- `eval_use_gather_object`: False
+- `eval_accumulation_steps`: None
+- `include_for_metrics`: []
+- `batch_eval_metrics`: False
+- `save_only_model`: False
+- `save_on_each_node`: False
+- `enable_jit_checkpoint`: False
+- `push_to_hub`: False
+- `hub_private_repo`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_always_push`: False
+- `hub_revision`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `restore_callback_states_from_checkpoint`: False
+- `full_determinism`: False
+- `seed`: 13
+- `data_seed`: None
+- `use_cpu`: False
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `parallelism_config`: None
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 2
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `dataloader_prefetch_factor`: None
+- `dataloader_multiprocessing_context`: None
+- `dataloader_in_order`: True
+- `remove_unused_columns`: True
+- `label_names`: None
+- `train_sampling_strategy`: random
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `ddp_static_graph`: None
+- `ddp_backend`: None
+- `ddp_timeout`: 1800
+- `fsdp`: None
+- `fsdp_config`: None
+- `deepspeed`: None
+- `debug`: []
+- `skip_memory_metrics`: True
+- `do_predict`: False
+- `resume_from_checkpoint`: None
+- `local_rank`: -1
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+- `warmup_ratio`: None
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss |
+|:------:|:----:|:-------------:|
+| 0.0947 | 50   | 1.6647        |
+| 0.1894 | 100  | 0.5485        |
+| 0.2841 | 150  | 0.4001        |
+| 0.3788 | 200  | 0.3659        |
+| 0.4735 | 250  | 0.3641        |
+| 0.5682 | 300  | 0.3502        |
+| 0.6629 | 350  | 0.3021        |
+| 0.7576 | 400  | 0.3171        |
+| 0.8523 | 450  | 0.2887        |
+| 0.9470 | 500  | 0.3043        |
+
+
+### Training Time
+- **Training**: 4.6 minutes
+
+### Framework Versions
+- Python: 3.14.4
+- Sentence Transformers: 6.1.0
+- Transformers: 5.20.2
+- PyTorch: 2.14.1+cu130
+- Accelerate: 1.15.0
+- Datasets: 5.1.0
+- Tokenizers: 0.23.3
+
+## Additional Resources
+
+- [Training and Finetuning Embedding Models with Sentence Transformers](https://huggingface.co/blog/train-sentence-transformers): the end-to-end guide for training or finetuning Sentence Transformer models.
+- [Introduction to Matryoshka Embedding Models](https://huggingface.co/blog/matryoshka): variable-size embeddings that can be truncated with minimal quality loss.
+- [Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval](https://huggingface.co/blog/embedding-quantization): post-training compression of embedding vectors.
+- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video models through the same API.
+- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): train multimodal embedding models, with a Visual Document Retrieval walkthrough.
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### CachedMultipleNegativesRankingLoss
+```bibtex
+@misc{gao2021scaling,
+    title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
+    author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
+    year={2021},
+    eprint={2101.06983},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG}
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{oord2019representationlearningcontrastivepredictive,
+      title={Representation Learning with Contrastive Predictive Coding},
+      author={Aaron van den Oord and Yazhe Li and Oriol Vinyals},
+      year={2019},
+      eprint={1807.03748},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/1807.03748},
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

v1.0/experiments/exploratory/models/ft-old-2015-16/config.json

@@ -0,0 +1,30 @@
+{
+  "add_cross_attention": false,
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.20.2",
+  "type_vocab_size": 1,
+  "use_cache": false,
+  "vocab_size": 250002
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "__version__": {
+    "pytorch": "2.14.1+cu130",
+    "sentence_transformers": "6.1.0",
+    "transformers": "5.20.2"
+  },
+  "default_prompt_name": null,
+  "model_type": "SentenceTransformer",
+  "prompts": {
+    "document": "",
+    "query": ""
+  },
+  "similarity_fn_name": "cosine"
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.base.modules.normalize.Normalize"
+  }
+]

v1.0/experiments/exploratory/models/ft-old-2015-16/parlir_train_meta.json

@@ -0,0 +1,13 @@
+{
+ "base": "intfloat/multilingual-e5-base",
+ "n_pairs": 16873,
+ "epochs": 1,
+ "batch_size": 32,
+ "lr": 2e-05,
+ "max_len": 512,
+ "seed": 13,
+ "hard_negatives": true,
+ "min_year": 2015,
+ "max_year": 2016,
+ "build": "data/build/v1.0"
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "feature-extraction",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "last_hidden_state"
+        }
+    },
+    "module_output_name": "token_embeddings"
+}

v1.0/experiments/exploratory/models/ft-old-2015-16/tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "is_local": false,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

v1.0/experiments/exploratory/runs/answer_dev_ft-datematched_text.meta.json

@@ -0,0 +1,14 @@
+{
+ "build": "data/build/v1.0",
+ "build_manifest_sha": "a63cc3ff183111c94a25c37c8b9b08f6b4782ce5449147d20cd8d7cd425c40ba",
+ "task": "answer",
+ "split": "dev",
+ "system": "me5-base-ft",
+ "field": "text",
+ "k": 100,
+ "k1": 0.9,
+ "b": 0.4,
+ "n_queries": 7735,
+ "n_docs": 76536,
+ "seconds": 84.8
+}

v1.0/experiments/exploratory/runs/answer_dev_ft-old-2015-16_text.meta.json

@@ -0,0 +1,14 @@
+{
+ "build": "data/build/v1.0",
+ "build_manifest_sha": "a63cc3ff183111c94a25c37c8b9b08f6b4782ce5449147d20cd8d7cd425c40ba",
+ "task": "answer",
+ "split": "dev",
+ "system": "me5-base-ft",
+ "field": "text",
+ "k": 100,
+ "k1": 0.9,
+ "b": 0.4,
+ "n_queries": 7735,
+ "n_docs": 76536,
+ "seconds": 84.7
+}

v1.0/experiments/exploratory/runs/answer_test_ft-datematched_text.meta.json

@@ -0,0 +1,14 @@
+{
+ "build": "data/build/v1.0",
+ "build_manifest_sha": "a63cc3ff183111c94a25c37c8b9b08f6b4782ce5449147d20cd8d7cd425c40ba",
+ "task": "answer",
+ "split": "test",
+ "system": "me5-base-ft",
+ "field": "text",
+ "k": 100,
+ "k1": 0.9,
+ "b": 0.4,
+ "n_queries": 10962,
+ "n_docs": 76536,
+ "seconds": 16.8
+}

v1.0/experiments/robustness/models/dm_s14/1_Pooling/config.json

@@ -0,0 +1,5 @@
+{
+    "embedding_dimension": 768,
+    "pooling_mode": "mean",
+    "include_prompt": true
+}

v1.0/experiments/robustness/models/dm_s14/2_Normalize/config.json

@@ -0,0 +1,4 @@
+{
+    "module_input_name": "sentence_embedding",
+    "module_output_name": "sentence_embedding"
+}

v1.0/experiments/robustness/models/dm_s14/README.md

@@ -0,0 +1,579 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:59612
+- loss:CachedMultipleNegativesRankingLoss
+- loss:MultipleNegativesRankingLoss
+base_model: intfloat/multilingual-e5-base
+widget:
+- source_sentence: 'query: Point of view regarding UK reform demands
+
+    On 11 November 2015, the UK Prime Minister, David Cameron, formally set out his
+    demands in a letter to the President of the European Council, stating that four
+    objectives lie at the heart of the UK’s renegotiations. What is the Council’s
+    perception in relation to the goals for reforming the UK’s membership of the EU,
+    including the restrictions on benefits for people coming to the UK?'
+  sentences:
+  - 'passage: The Council dealt with the UK reform demands as part of the preparations
+    for the European Council. The Council supported the aim of finding mutually satisfactory
+    solutions in all four areas mentioned in the UK Prime Minister''s letter of 10
+    November 2015. However, the Council is not the institution in charge of finding
+    a solution to this issue. The New Settlement for the United Kingdom within the
+    European Union was agreed at the level of Heads of State or Government and the
+    President of the Commission at the meeting of the European Council of 18 and 19
+    February 2016. The set of arrangements constituting this settlement was published
+    in the Official Journal of the European Union[1].
+
+    [1] OJ C 69 I, 23.2.2016, p. 1.'
+  - 'passage: President Juncker has repeatedly said that he wants to achieve a deal
+    that is fair for the UK and fair for all other Member States. The Commission and
+    the Council are actively working on the requests of the UK as set out in Prime
+    Minister Cameron''s letter to President Tusk of 10 November 2015.
+
+    The Commission does not speculate on the results of the UK referendum.'
+  - 'passage: The Commission is regularly informed about the situation at the Spanish-Gibraltar
+    border, including on delays reported by citizens upon entry or exit to Spain.
+
+    On 30 July 2014 the Commission addressed requests for additional measures to both
+    Spain and the United Kingdom to be implemented without delay in order to reduce
+    the waiting time. One of the important measures requested from Spain is to optimise
+    the risk-based profiling and to adapt the checks accordingly. The Commission recently
+    received the reply from Spain. It will proceed to its analysis before assessing
+    the situation at this border again.'
+- source_sentence: 'query: Compliance with Directive 2012/47/EU
+
+    In response to Question [REF], Mr Nelli Feroci answered on behalf of the Commission:
+    ''On the basis of the first analysis of transposition measures notified by Spain
+    as well as of available information, the Commission considers prima facie that
+    Directive 2012/47/EU has been correctly transposed by Spain.''
+
+    1. Has the Commission now completed the full analysis of the transposition measures
+    notified by Spain?
+
+    2. Is the Commission satisfied with the result?'
+  sentences:
+  - 'passage: It is not for the Council to comment on a legislative act that has been
+    adopted by the European Parliament and by the Council in the ordinary legislative
+    procedure.'
+  - 'passage: On the basis of the first analysis of transposition measures notified
+    by Spain as well as of available information, the Commission considers prima facie
+    that Directive 2012/47/EU[1] has been correctly transposed by Spain.
+
+    [1] Directive 2012/47/EU of 14 December 2012 amending Directive 2009/43/EC of
+    the European Parliament and of the Council regards the list of defence-related
+    products'
+  - 'passage: After having carried out a more thorough analysis of the transposition
+    measures notified by Spain related to Directive 2012/47/EC, the Commission has
+    not found any reason that would justify launching an infringement procedure. In
+    line with the provisions of Directive 2009/43/EC on intra-community transfer of
+    defence-related products, the list of defence-related products in annex of the
+    Directive has to be regularly updated in order to strictly reflect the Common
+    Military List of the European Union (CML) annually adopted by the Council. Directive
+    2012/47/EC updated annex I of the Directive 2009/43/EC in accordance with the
+    CML of 2012. Directive 2012/47/EC has by now been substituted by Directive 2014/108/EU.'
+- source_sentence: 'query: EU politicians banned from third countries
+
+    Does the Council maintain a list of which EU politicians are currently banned
+    from nations which are not members of the European Union? If so, please provide
+    details.'
+  sentences:
+  - 'passage: Rules and practices on the cooling-off periods applicable to national
+    politicians and senior civil servants are of the competence of Member States.
+    The European Union''s support competence in the administrative cooperation field
+    does not empower it to harmonise those national rules and practices.
+
+    The Commission has its own body of rules (in particular, the Code of Conduct for
+    Commissioners and Staff Regulations for EU officials) as regards conflicts of
+    interest and post mandate service activities. The Commission''s perception is
+    that there is a general understanding amongst administrations that a cooling-off
+    period is an efficient tool to cater for the risk of conflicts of interest that
+    may stem from post mandate service activities. Such restriction may be imposed
+    with due consideration for the principle of proportionality in particular in light
+    of the right of every individual to pursue a freely chosen or accepted occupation
+    as enshrined in Article 15 of the Charter of Fundamental Rights of the EU.
+
+    However, the Commission does not have any detailed information on the cooling-off
+    periods applied in each EU Member States for politicians and senior civil servants.
+    Considerable resources would be needed to gather accurate and exhaustive information
+    on the rules and practices of every single Member State.'
+  - 'passage: For an outermost region such as the Canary Islands the EU Solidarity
+    Fund could be activated under two main conditions. Firstly, total direct damage
+    caused by the disaster would have to exceed 1% of the regional Gross Domestic
+    Product at NUTS2 level. For the Canary Islands this threshold currently amounts
+    to EUR 407.2 million. Secondly, the competent national authorities of Spain would
+    have to present an application for Solidarity Fund assistance to the Commission
+    within 12 weeks of the disaster happening. Until now, the Spanish authorities
+    have not submitted an application or indicated that they intend doing so.'
+  - 'passage: The information requested by the Honourable Member is not available
+    to the Council.'
+- source_sentence: 'query: Europe for Citizens - West Midlands
+
+    1. Can the Commission provide details of what funding and initiatives it has provided
+    through the Europe for Citizens programme in the West Midlands in the period 2009-2014?
+
+    2. Can the Commission indicate which of these programmes are operating at present?
+
+    3. Can the Commission also provide details of any planned funding to be provided
+    in the West Midlands through the Europe for Citizens programme in the next funding
+    period?'
+  sentences:
+  - 'passage: According to FRONTEX, 11 639 migrants illegally entered on the islands
+    of Greece via Turkey from 20 March 2016 to 3 July 2016.
+
+    From 4 April 2016 - planned date for the first returns under the statement - to
+    6 July 2016, 468 migrants were readmitted to Turkey under the EU-Turkey Statement
+    of 18 March 2016.
+
+    More generally, the Commission would like to refer the Honourable Member to its
+    reports on the implementation of the EU-Turkey statement.[1]
+
+    [1] In particular the Second Report on the progress made in the implementation
+    of the EU-Turkey Statement, COM(2016) 349 final'
+  - 'passage: The Commission would like to inform the Honourable Member that the West
+    Midlands region (UK) plays an active role in the Europe for Citizens Programme,
+    in particular in the area of town-twinning. Between 2009 and 2013, the municipalities
+    of Stafford, Leek, Eardisland, Leominster and Worcester situated in the West Midlands
+    Region have received grants from the Europe for Citizens Programme for town-twinning
+    projects with twin towns, such as Este (Italy), Bad Windsheim (Germany) or Pertuis
+    (France).
+
+    The municipality of Leek received three grants for a total amount of EUR 23,964,
+    the Stafford and Tarragona Twinning association received a grant of EUR 17,945
+    and Eardisland, Leominster and Worcester EUR 5,000 for small-scale town-twinning
+    projects. All selected projects were implemented successfully.'
+  - 'passage: 1. The funding shown in Annex I was provided through the Europe for
+    Citizens programme in the West Midlands in the period 2009-2014
+
+    2. The Europe for Citizens programme 2014-2020 is the successor to the Europe
+    for Citizens Programme 2007-2013.
+
+    3. Co-financing under the Europe for Citizens Programme is granted on the basis
+    of calls for proposals and the Commission thus cannot know in advance which projects
+    will be selected.'
+- source_sentence: 'query: Destruction of a Russian plane by the Turkish air force
+
+    The Turkish air force shot down a Russian plane on Tuesday morning. The exact
+    circumstances have yet to be established. Nevertheless, Turkey is clearly more
+    inclined to take action against Russian or Kurdish forces than against Islamic
+    State.
+
+    While a grand coalition is currently being formed to combat Islamic State, Turkey’s
+    role in the region is murkier than ever. This confirms that Turkey is not a reliable
+    interlocutor, contrary to what Angela Merkel and François Hollande would have
+    us believe.
+
+    In the face of this reprehensible act of war, the Council should take up a clear
+    position vis-à-vis the Erdoğan government.
+
+    Taking the current situation into account, does the Council intend to reconsider
+    the policy on Turkey that it has pursued up to now?'
+  sentences:
+  - 'passage: Regarding the Council''s policy on Turkey, the Honourable Member is
+    invited to refer to the Council''s reply to Written Question [REF].'
+  - 'passage: After the downing of a Russian jet plane at the Turkish-Syrian border,
+    the EU High Representative Federica Mogherini, in separate phone calls to both
+    the Russian and the Turkish Foreign Ministers stressed the need to avoid further
+    escalation, preserve the diplomatic talks on Syria and unite forces against Da''esh.
+
+    The EU continues to actively support the UN-led international efforts to find
+    a political solution to the Syrian conflict, and is proactively engaging regional
+    and international partners. Both Turkey and Russia are part of the International
+    Syria Support Group (ISGG) and their role remains critical for the search for
+    a solution to the Syria crisis. We expect both Turkey and Russia to actively support
+    the ongoing cessation of hostilities and the search for a political solution.'
+  - 'passage: Equal access to education irrespective of gender is a priority for the
+    EU. This priority is mainstreamed in all EU bilateral cooperation programmes in
+    education.
+
+    As regards to the actions taken to improve girls and women access to education,
+    the Commission would refer the Honourable Member to its answer to written question
+
+    [REF][1].
+
+    [1] http://www.europarl.europa.eu/plenary/en/parliamentary-questions.html'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on intfloat/multilingual-e5-base
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base). It maps inputs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) <!-- at revision d128750597153bb5987e10b1c3493a34e5a4502a -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Supported Modality:** Text
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'XLMRobertaModel'})
+  (1): Pooling({'embedding_dimension': 768, 'pooling_mode': 'mean', 'include_prompt': True})
+  (2): Normalize({'module_input_name': 'sentence_embedding', 'module_output_name': 'sentence_embedding'})
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'query: Destruction of a Russian plane by the Turkish air force\nThe Turkish air force shot down a Russian plane on Tuesday morning. The exact circumstances have yet to be established. Nevertheless, Turkey is clearly more inclined to take action against Russian or Kurdish forces than against Islamic State.\nWhile a grand coalition is currently being formed to combat Islamic State, Turkey’s role in the region is murkier than ever. This confirms that Turkey is not a reliable interlocutor, contrary to what Angela Merkel and François Hollande would have us believe.\nIn the face of this reprehensible act of war, the Council should take up a clear position vis-à-vis the Erdoğan government.\nTaking the current situation into account, does the Council intend to reconsider the policy on Turkey that it has pursued up to now?',
+    "passage: Regarding the Council's policy on Turkey, the Honourable Member is invited to refer to the Council's reply to Written Question [REF].",
+    "passage: After the downing of a Russian jet plane at the Turkish-Syrian border, the EU High Representative Federica Mogherini, in separate phone calls to both the Russian and the Turkish Foreign Ministers stressed the need to avoid further escalation, preserve the diplomatic talks on Syria and unite forces against Da'esh.\nThe EU continues to actively support the UN-led international efforts to find a political solution to the Syrian conflict, and is proactively engaging regional and international partners. Both Turkey and Russia are part of the International Syria Support Group (ISGG) and their role remains critical for the search for a solution to the Syria crisis. We expect both Turkey and Russia to actively support the ongoing cessation of hostilities and the search for a political solution.",
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities)
+# tensor([[1.0000, 0.8275, 0.4647],
+#         [0.8275, 1.0000, 0.2871],
+#         [0.4647, 0.2871, 1.0000]])
+```
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 59,612 training samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 100 samples:
+  |          | anchor                                                                               | positive                                                                             | negative                                                                             |
+  |:---------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type     | string                                                                               | string                                                                               | string                                                                               |
+  | modality | text                                                                                 | text                                                                                 | text                                                                                 |
+  | details  | <ul><li>min: 33 tokens</li><li>mean: 238.46 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 23 tokens</li><li>mean: 352.27 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 98 tokens</li><li>mean: 392.77 tokens</li><li>max: 512 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>query: The role of merit in unequal societies<br>Inequality is one of the most controversial topics in the European Union, as it has returned to levels seen in the early decades of the last century, albeit with the difference that in today’s Europe the welfare state protects the less privileged.<br>Health care and education are almost free, pensions are often higher than the contributions paid, and unemployment benefit in some countries is higher than in others. Therefore equal opportunities need to be guaranteed for everybody.<br>Equal incentives are needed, rewarding merit and endeavour, especially to protect minorities that find themselves unable to compete despite their endeavour and commitment.<br>The welfare state, which was created for this purpose, must therefore do everything it can to help.<br>Can the Commission say what instruments it considers necessary to eliminate such inequalities and ensure that everybody enjoys equal opportunities?</code>                                                | <code>passage: The European Commission works alongside Member States (MS) to foster equality of opportunity for all and promotes the active inclusion and full participation of vulnerable groups in society.<br>The EU legal framework for equal and anti-discrimination includes the Racial Equality Directive, implementing the principle of equal treatment between persons irrespective of racial or ethnic origin in many areas of social life, and the Employment Equality Directive, which establishes a general framework for equal treatment in employment and occupation.<br>In addition, the Commission:<br> In the context of the European Semester, monitors Member States' policies and provides policy guidance in its annual Country-Specific Recommendations;<br> Supports the implementation of MS' social policies, also through funding[1], e.g. the European Social Fund (ESF), the Youth Employment Initiative, the Fund for European Aid to the Most Deprived (FEAD), the EU Programme for Employment and Social Innovation (EaS...</code> | <code>passage: The Strategy on equality between women and men 2010-2015[1] (Strategy) addresses women's higher poverty risk, particularly within its strand on Equal Economic Independence. One of the key actions is the promotion of gender equality in implementing the Europe 2020 strategy[2]. The Commission’s 2012 White Paper on Pensions provides guidance to Member States on closing the gender pension gap, and the 2013 Social Investment Package urges Member States to improve the social and labour market integration of women.<br>Within the European Semester, the Commission has issued Country Specific Recommendations reflecting these policy priorities. In 2014, 14 Member States received CSRs to: promote female employment through the provision of child-care facilities and the reduction of fiscal disincentives; equalise the pensionable age between women and men; address the poverty risk for older women and ensure equal opportunities for vulnerable individuals. Other actions of the Strategy include th...</code>    |
+  | <code>query: EU assistance programme for the Turkish Cypriot community seeking the reunification of Cyprus<br>Since 2006, the European Commission has been approving assistance programmes for the Turkish Cypriot community in Cyprus. The 2021 action programme, totalling EUR 30.7 million, seeks to facilitate the reunification of Cyprus, focusing in particular on the economic integration of the island and closer contacts between the two communities with each other and with the EU. From 2006 to 2021, EUR 623 million was allocated for projects to support confidence-building measures and continue substantial funding for the Committee on Missing Persons and the Technical Committee on Cultural Heritage.<br>However while the aid programme is seeking to facilitate the reunification of the island, the Turkish Cypriot side, with the support and guidance of Turkey, is calling for a 'two-state solution' in Cyprus, contrary to UN Security Council resolutions and EU law. Moreover, a further breach of UN Security C...</code> | <code>passage: The overall objective of the Aid Programme under Council Regulation (EC) No 389/2006[1] is to facilitate the reunification of Cyprus through the implementation of projects under the six objectives outlined in the Regulation.<br>An external evaluation, which will be published shortly, has examined the Aid Programme in the 2013-2018 period against six evaluation criteria: relevance, effectiveness, efficiency, coherence, EU added value and sustainability. The evaluation assessed a sample of 22 interventions that covered all six objectives of the Aid Programme, corresponding to around 60% of the total operational budget of EUR 199 million. The evaluation concluded that the Aid Programme remains relevant due to the persisting gap in socio-economic development and the absence of a comprehensive settlement. It also found that the programme was generally able to achieve the intended results despite, in some cases, delays and sustainability issues due to capacity problems on the beneficia...</code>          | <code>passage: The best way forward to resolve the Cyprus problem is through a resumption of formal negotiations of a comprehensive settlement. The EU remains fully committed to the comprehensive settlement based on a bicommunal, bizonal federation with political equality, in accordance with the relevant United Nations (UN) Security Council Resolutions and the principles on which the EU is founded[1].<br>The EU will continue to play an active role in supporting the process. The Commission implements an aid programme[2] to facilitate the reunification of Cyprus by encouraging the economic development of the Turkish Cypriot community with particular emphasis on the economic integration of the island, on improving contacts between the two communities and with the EU, and on preparation for the EU acquis. Between 2006 and now, about EUR 600 million have been allocated to this programme.<br>The commitment of all parties involved to creating the conditions for the comprehensive settlement remains crucia...</code> |
+  | <code>query: VP/HR - Iran compulsory dress code<br>In December 2017, a recent wave of protests were sparked when a woman standing on Teheran’s Revolution Street posted a picture on social media of herself without a headscarf. Her peaceful protest generated many others. Including the original protester, numerous other women were arrested and charged with things like ‘openly committing a sinful act’ and ‘encouraging immorality or prostitution’, which can earn them up to ten years in prison if they are convicted. Iran’s strict dress code violates women’s right to freedom of expression and religion.<br>What can be done to encourage Iran to be more lenient with the dress code?</code>                                                                                                                                                                                                                                                                                                                                                | <code>passage: The wave of protests in December 2017 which were driven mostly by economic and social grievances, have sparked a debate in the country on several issues including on the compulsory Islamic dress code for women. President Rouhani appealed for greater personal freedoms at the annual celebration of the Islamic Revolution on 11 February 2018 and spoke in favor of organising referendums on certain topics of debate in Iran. Also the Vice-President for Women and Family Affairs, Masoumeh Ebtekar, has emphasized the need for a dialogue with the youth on the mandatory hijab and to use methods that are lawful instead of using police force.<br>The EU attaches high importance to human rights and fundamental freedoms in Iran. During the latest round of the High Level Dialogue with Iran, which took place in November 2017 in Tehran, the rights of women were one of the key topics discussed. In this context, the EU has also met with the Vice-President for Women and Family Affairs, Masoumeh Ebtekar...</code>          | <code>passage: The waves of protests in Iran which have taken place in Iran since the beginning of 2018 have sparked a debate in the country on several issues including on the compulsory Islamic dress code for women. President Rouhani appealed for greater personal freedoms at the annual celebration of the Islamic Revolution on 11 February 2018 and spoke in favor of organising referendums on certain topics of debate in Iran. Also the Vice-President for Women and Family Affairs, Masoumeh Ebtekar, has emphasized the need for a dialogue with the youth on the mandatory hijab and to use methods that are lawful instead of using police force.<br>The EU attaches high importance to human rights and fundamental freedoms in Iran. During the latest round of the High Level Dialogue with Iran, which took place in November 2017 in Tehran, the rights of women were one of the key topics discussed. In this context, the EU has also met with the Vice-President for Women and Family Affairs, Masoumeh Ebtekar and agre...</code>    |
+* Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim",
+      "mini_batch_size": 8,
+      "mini_batch_num_tokens": null,
+      "gather_across_devices": false,
+      "directions": [
+          "query_to_doc"
+      ],
+      "partition_mode": "joint",
+      "hardness_mode": null,
+      "hardness_strength": 0.0
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `learning_rate`: 2e-05
+- `warmup_steps`: 0.1
+- `fp16`: True
+- `seed`: 14
+- `dataloader_num_workers`: 2
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `learning_rate`: 2e-05
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: None
+- `warmup_steps`: 0.1
+- `optim`: adamw_torch_fused
+- `optim_args`: None
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `optim_target_modules`: None
+- `gradient_accumulation_steps`: 1
+- `average_tokens_across_devices`: True
+- `max_grad_norm`: 1.0
+- `label_smoothing_factor`: 0.0
+- `bf16`: False
+- `fp16`: True
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `use_cache`: False
+- `neftune_noise_alpha`: None
+- `torch_empty_cache_steps`: None
+- `auto_find_batch_size`: False
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `include_num_input_tokens_seen`: no
+- `log_level`: passive
+- `log_level_replica`: warning
+- `disable_tqdm`: False
+- `project`: huggingface
+- `trackio_space_id`: None
+- `trackio_bucket_id`: None
+- `trackio_static_space_id`: None
+- `per_device_eval_batch_size`: 8
+- `prediction_loss_only`: True
+- `eval_on_start`: False
+- `eval_do_concat_batches`: True
+- `eval_use_gather_object`: False
+- `eval_accumulation_steps`: None
+- `include_for_metrics`: []
+- `batch_eval_metrics`: False
+- `save_only_model`: False
+- `save_on_each_node`: False
+- `enable_jit_checkpoint`: False
+- `push_to_hub`: False
+- `hub_private_repo`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_always_push`: False
+- `hub_revision`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `restore_callback_states_from_checkpoint`: False
+- `full_determinism`: False
+- `seed`: 14
+- `data_seed`: None
+- `use_cpu`: False
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `parallelism_config`: None
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 2
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `dataloader_prefetch_factor`: None
+- `dataloader_multiprocessing_context`: None
+- `dataloader_in_order`: True
+- `remove_unused_columns`: True
+- `label_names`: None
+- `train_sampling_strategy`: random
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `ddp_static_graph`: None
+- `ddp_backend`: None
+- `ddp_timeout`: 1800
+- `fsdp`: None
+- `fsdp_config`: None
+- `deepspeed`: None
+- `debug`: []
+- `skip_memory_metrics`: True
+- `do_predict`: False
+- `resume_from_checkpoint`: None
+- `local_rank`: -1
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+- `warmup_ratio`: None
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss |
+|:------:|:----:|:-------------:|
+| 0.0268 | 50   | 2.2481        |
+| 0.0537 | 100  | 0.6475        |
+| 0.0805 | 150  | 0.4511        |
+| 0.1074 | 200  | 0.4033        |
+| 0.1342 | 250  | 0.3842        |
+| 0.1610 | 300  | 0.3371        |
+| 0.1879 | 350  | 0.3596        |
+| 0.2147 | 400  | 0.3460        |
+| 0.2415 | 450  | 0.3164        |
+| 0.2684 | 500  | 0.3371        |
+| 0.2952 | 550  | 0.2960        |
+| 0.3221 | 600  | 0.3085        |
+| 0.3489 | 650  | 0.3128        |
+| 0.3757 | 700  | 0.2875        |
+| 0.4026 | 750  | 0.2928        |
+| 0.4294 | 800  | 0.2769        |
+| 0.4563 | 850  | 0.2924        |
+| 0.4831 | 900  | 0.2833        |
+| 0.5099 | 950  | 0.2829        |
+| 0.5368 | 1000 | 0.3053        |
+| 0.5636 | 1050 | 0.2766        |
+| 0.5904 | 1100 | 0.2984        |
+| 0.6173 | 1150 | 0.2698        |
+| 0.6441 | 1200 | 0.2525        |
+| 0.6710 | 1250 | 0.2651        |
+| 0.6978 | 1300 | 0.2811        |
+| 0.7246 | 1350 | 0.2733        |
+| 0.7515 | 1400 | 0.2428        |
+| 0.7783 | 1450 | 0.2828        |
+| 0.8052 | 1500 | 0.2765        |
+| 0.8320 | 1550 | 0.2523        |
+| 0.8588 | 1600 | 0.2672        |
+| 0.8857 | 1650 | 0.2838        |
+| 0.9125 | 1700 | 0.2467        |
+| 0.9393 | 1750 | 0.2746        |
+| 0.9662 | 1800 | 0.2511        |
+| 0.9930 | 1850 | 0.2642        |
+
+
+### Training Time
+- **Training**: 16.0 minutes
+
+### Framework Versions
+- Python: 3.14.4
+- Sentence Transformers: 6.1.0
+- Transformers: 5.20.2
+- PyTorch: 2.14.1+cu130
+- Accelerate: 1.15.0
+- Datasets: 5.1.0
+- Tokenizers: 0.23.3
+
+## Additional Resources
+
+- [Training and Finetuning Embedding Models with Sentence Transformers](https://huggingface.co/blog/train-sentence-transformers): the end-to-end guide for training or finetuning Sentence Transformer models.
+- [Introduction to Matryoshka Embedding Models](https://huggingface.co/blog/matryoshka): variable-size embeddings that can be truncated with minimal quality loss.
+- [Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval](https://huggingface.co/blog/embedding-quantization): post-training compression of embedding vectors.
+- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video models through the same API.
+- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): train multimodal embedding models, with a Visual Document Retrieval walkthrough.
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### CachedMultipleNegativesRankingLoss
+```bibtex
+@misc{gao2021scaling,
+    title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
+    author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
+    year={2021},
+    eprint={2101.06983},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG}
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{oord2019representationlearningcontrastivepredictive,
+      title={Representation Learning with Contrastive Predictive Coding},
+      author={Aaron van den Oord and Yazhe Li and Oriol Vinyals},
+      year={2019},
+      eprint={1807.03748},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/1807.03748},
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

v1.0/experiments/robustness/models/dm_s14/config.json

@@ -0,0 +1,30 @@
+{
+  "add_cross_attention": false,
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.20.2",
+  "type_vocab_size": 1,
+  "use_cache": false,
+  "vocab_size": 250002
+}

v1.0/experiments/robustness/models/dm_s14/config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "__version__": {
+    "pytorch": "2.14.1+cu130",
+    "sentence_transformers": "6.1.0",
+    "transformers": "5.20.2"
+  },
+  "default_prompt_name": null,
+  "model_type": "SentenceTransformer",
+  "prompts": {
+    "document": "",
+    "query": ""
+  },
+  "similarity_fn_name": "cosine"
+}

v1.0/experiments/robustness/models/dm_s14/modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.base.modules.normalize.Normalize"
+  }
+]

v1.0/experiments/robustness/models/dm_s14/parlir_train_meta.json

@@ -0,0 +1,19 @@
+{
+ "base": "intfloat/multilingual-e5-base",
+ "n_pairs": 59612,
+ "epochs": 1,
+ "batch_size": 32,
+ "lr": 2e-05,
+ "max_len": 512,
+ "seed": 14,
+ "hard_negatives": true,
+ "min_year": 0,
+ "max_year": 0,
+ "hardneg_window_days": 365,
+ "negatives": "bm25",
+ "negative_stats": {
+  "date_matched_bm25": 58288,
+  "date_matched_random": 1324
+ },
+ "build": "data/build/v1.0"
+}

v1.0/experiments/robustness/models/dm_s14/sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "feature-extraction",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "last_hidden_state"
+        }
+    },
+    "module_output_name": "token_embeddings"
+}

v1.0/experiments/robustness/models/dm_s14/tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "is_local": false,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

v1.0/experiments/robustness/models/dm_s15/1_Pooling/config.json

@@ -0,0 +1,5 @@
+{
+    "embedding_dimension": 768,
+    "pooling_mode": "mean",
+    "include_prompt": true
+}

v1.0/experiments/robustness/models/dm_s15/2_Normalize/config.json

@@ -0,0 +1,4 @@
+{
+    "module_input_name": "sentence_embedding",
+    "module_output_name": "sentence_embedding"
+}

v1.0/experiments/robustness/models/dm_s15/README.md

@@ -0,0 +1,581 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- dense
+- generated_from_trainer
+- dataset_size:59612
+- loss:CachedMultipleNegativesRankingLoss
+- loss:MultipleNegativesRankingLoss
+base_model: intfloat/multilingual-e5-base
+widget:
+- source_sentence: 'query: Erasmus students at Liverpool John Moores University
+
+    Could the Commission provide details of how many Erasmus students studied at Liverpool
+    John Moores University between 2004 and 2014?'
+  sentences:
+  - 'passage: The Jean Monnet Action offers chairs and modules to support scholars
+    in developing European Union studies.
+
+    However, no scholars from Liverpool John Moores University have benefitted from
+    Jean Monnet Action''s support between 2004 and 2014, nor before.'
+  - 'passage: r Hogano
+
+    n behalf of the Commission(16.2.2018)
+
+    The Commission is aware of the widespread use in Mexico of the term ''manchego''
+    associated to a type of cheese whose c
+
+    haracteristics greatly differ from the EU geographical indication ''Queso Manchego'',
+    which has never been protected in Mexico.
+
+    ''Queso Manchego'' is one of the geographical indications submitted by the EU
+    to Mexico for protection under the modernised F
+
+    ree Trade Agreement. Negotiations on geographical indications are on-going and
+    the Commisson will make all efforts to obtain the most satisfactory result possible
+    on every term submitted to Mexico.'
+  - 'passage: Statistics for Erasmus mobility broken down at the level of detail requested
+    by the Honourable Member are available only since the beginning of the Lifelong
+    Learning Programme in 2007. Since the academic year 2007/2008 until the academic
+    year 2012/2013, the last year for which data are currently available, the four
+    higher education institutions received the following numbers of Erasmus students
+    :
+
+    Manchester Metropolitan University: 1.631
+
+    Salford University: 1.299
+
+    University of Liverpool: 823
+
+    Liverpool John Moores University: 447
+
+    The full breakdown of the data by academic year and institution of destination
+    is attached.'
+- source_sentence: 'query: Seat of the European Parliament
+
+    What are the Council’s intentions as regards the seat of the European Parliament?
+    Though Parliament extends over three cities, only one has genuinely been regarded
+    as its seat from the outset: Strasbourg.
+
+    Transport links to and from Strasbourg are improving all the time - the high-speed
+    rail link and the new airlines there are major factors in this - and ensuring
+    security on the Strasbourg site is much more straightforward than in Brussels.
+
+    Can the Council make a clear statement in favour of upgrading Strasbourg?'
+  sentences:
+  - 'passage: Article 341 of the TFEU provides that the seat of the institutions of
+    the Union shall be determined by common accord of the Governments of the Member
+    States. In accordance with paragraph (a) of the sole article of the sixth protocol
+    annexed to the Treaties, ''the European Parliament shall have its seat in Strasbourg
+    where the 12 periods of monthly plenary sessions, including the budget session,
+    shall be held.''
+
+    With regard to the questions posed by the Honourable Member, the Council has not
+    discussed these issues and is not in a position to give an answer.'
+  - 'passage: The Commission has referred the questions on how the European Food Safety
+    Authority (EFSA) strives to ensure that its workforce is representative of European
+    citizens to the EFSA, as the Authority is an independent EU agency with responsibility
+    for its staff matters. The response will be communicated directly to the Honourable
+    Member as soon as possible.'
+  - 'passage: The matter of the location of the seats of the institutions is addressed
+    by Protocol No 6 to the Treaty.
+
+    It is not for the Council to comment on the seat of the European Parliament.'
+- source_sentence: 'query: What more can the European Fisheries Control Agency do
+    to have a workforce that is representative of EU citizens?
+
+    Previously, the Commission has stated that ‘the Commission strives to be representative
+    of the increasingly diverse European citizens it serves’ (response to Written
+    Questions [REF], [REF] and [REF]).
+
+    How does the European Fisheries Control Agency think it’s currently doing on having
+    a workforce that is representative of EU citizens?
+
+    What more can the European Fisheries Control Agency do to be more representative
+    of EU citizens?'
+  sentences:
+  - 'passage: The Commission has asked the European Fisheries Control Agency (EFCA)
+    to provide a response to the question raised by the Honourable Member. The Agency''s
+    reply will be sent by the Commission to the Honourable Member as soon as possible.'
+  - 'passage: As a follow-up to its recent response to written questions [REF] and
+    [REF][1] on how the European Food Safety Authority (EFSA) strives to ensure that
+    its workforce is representative of European citizens, the Commission has provided
+    to the Honourable Member on behalf of the EFSA, an extensive list of activities
+    EFSA is undertaking to ensure that its workforce is representative of the European
+    Union citizens.
+
+    To respond to the present question, the Commission has asked EFSA to provide 10
+    examples of its efforts to be representative of EU citizens in practice. The response
+    will be communicated directly to the Honourable Member as soon as possible.
+
+    [1] http://www.europarl.europa.eu/plenary/en/parliamentary-questions.html'
+  - 'passage: The President of the European Council has undertaken to reply to parliamentary
+    questions in so far as they concern his own political activities. As discussions
+    held in the context of the EU-Ukraine Summit of 27 April 2015 fall outside the
+    scope of this commitment, the President of the European Council is not in a position
+    to answer the question put by the Honourable Members.'
+- source_sentence: 'query: Update on the case involving two Italian marines
+
+    Can the Commission report on how discussions are progressing with the Indian authorities
+    on the case involving two Italian marines - a sequence of events which started
+    in 2012 but seems no closer to a conclusion that would definitively return the
+    two navy riflemen to Italy?'
+  sentences:
+  - 'passage: The EU has been following the case of the two Italian marines since
+    its beginning, in close contact with both the Italian and Indian authorities.
+    The High Representative Catherine Ashton has consistently raised this issue in
+    her encounters with representatives of the Indian government in recent months.
+
+    On all these occasions the EU has encouraged India to find a rapid and satisfactory
+    outcome to this dispute as soon as possible, based on the UN Convention on the
+    Law of the Sea and international law. The EU has also stressed several times that
+    the delays in the trial against the two marines are totally unacceptable.
+
+    The EU welcomes the decision of India''s Supreme Court to let one of the two marines
+    go back to Italy to receive medical treatment after he suffered a stroke at the
+    end of August.'
+  - 'passage: The Commission is aware of mounting price pressure in the dairy sector
+    since the beginning of the year, following a period of historically high prices,
+    and as a consequence of oversupply.
+
+    The Commission does not rate Member States on the application of the “Milk Package”
+    For details about how Member States and operators make use of the “Milk Package”
+    the Honourable Member is referred to the Commission Report of 13.6.2014[1].
+
+    The Commission can confirm that Spain has satisfactorily implemented the Rural
+    Development measures on ''Modernisation of agricultural holdings'' and ''Increasing
+    the added value of basic agricultural and forestry production''.
+
+    [1] COM(2014)354 http://ec.europa.eu/agriculture/milk/milk-package/com-2014-354_en.pdf'
+  - 'passage: The EU has been following the case of the two Italian marines in close
+    contact with the Italian government and has repeatedly called for a swift solution
+    to this longstanding case in accordance with international law and the UN Convention
+    on the Law of the Sea (UNCLOS). On 9th April 2015 the Indian Supreme Court decided
+    to extend Mr. Latorre''s medical leave in Italy until 15th July 2015.
+
+    The EU continues to support efforts towards a mutually acceptable solution that
+    would allow the return of the two marines.'
+- source_sentence: 'query: Atlantic Trench
+
+    In its answer to question [REF] from this Member, the Commission noted that, under
+    Article 35 of the Euratom Treaty, the Commission can verify Spain’s monitoring
+    of marine radioactivity, but that, currently, ‘it is not included in the Commission
+    verification mission planning for 2018-2020’.
+
+    1. Is there any possibility of including it in said planning or in the next one?
+
+    2. What steps are required to ensure this monitoring is included in the verifications
+    conducted by the Commission?'
+  sentences:
+  - 'passage: Implementation of Article 16 of the Tobacco Products Directive[1] is
+    an ongoing process. Last year the Commission published a feasibility study[2]
+    which was followed by a targeted stakeholder consultation. The feasibility study
+    contained an initial mapping of available technologies for security features.
+    The preparatory work for drafting the necessary implementing acts continues and
+    will include a public consultation, stakeholder workshops and an implementation
+    study.
+
+    [1] Directive 2014/40/EU of 3 April 2014, OJ L 127, 29.4.2014, p. 1
+
+    [2] http://ec.europa.eu/health/tobacco/docs/2015_tpd_tracking_tracing_frep_en.pdf'
+  - 'passage: The Commission has not received any evidence that new studies on the
+    state of radioactive waste in the Atlantic trenches are necessary.
+
+    Monitoring of marine radioactivity by Spain can be covered by verification mission
+    by the Commission under Article 35 of the Euratom Treaty. Currently, it is not
+    included in the Commission verification mission planning for 2018-2020.'
+  - 'passage: Euratom Article 35 verifications are carried out according to a three-year
+    rolling programme, which is updated by the Commission services every six months.
+    This programme takes into account general principles such as: adequate coverage
+    of all Member States; inclusion of installations across the complete spectrum
+    of the nuclear fuel cycle as well as nation-wide monitoring systems. Verification
+    targets are selected according to their radiological significance or public interest.
+
+    The Commission services have, in June 2018, identified marine monitoring on the
+    coast of Galicia as a verification target in 2019. The Commission is following
+    the situation and will review the verification planning in December 2018, where
+    verification targets for 2019 will be confirmed.'
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on intfloat/multilingual-e5-base
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base). It maps inputs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) <!-- at revision d128750597153bb5987e10b1c3493a34e5a4502a -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Supported Modality:** Text
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'XLMRobertaModel'})
+  (1): Pooling({'embedding_dimension': 768, 'pooling_mode': 'mean', 'include_prompt': True})
+  (2): Normalize({'module_input_name': 'sentence_embedding', 'module_output_name': 'sentence_embedding'})
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'query: Atlantic Trench\nIn its answer to question [REF] from this Member, the Commission noted that, under Article 35 of the Euratom Treaty, the Commission can verify Spain’s monitoring of marine radioactivity, but that, currently, ‘it is not included in the Commission verification mission planning for 2018-2020’.\n1. Is there any possibility of including it in said planning or in the next one?\n2. What steps are required to ensure this monitoring is included in the verifications conducted by the Commission?',
+    'passage: Euratom Article 35 verifications are carried out according to a three-year rolling programme, which is updated by the Commission services every six months. This programme takes into account general principles such as: adequate coverage of all Member States; inclusion of installations across the complete spectrum of the nuclear fuel cycle as well as nation-wide monitoring systems. Verification targets are selected according to their radiological significance or public interest.\nThe Commission services have, in June 2018, identified marine monitoring on the coast of Galicia as a verification target in 2019. The Commission is following the situation and will review the verification planning in December 2018, where verification targets for 2019 will be confirmed.',
+    'passage: The Commission has not received any evidence that new studies on the state of radioactive waste in the Atlantic trenches are necessary.\nMonitoring of marine radioactivity by Spain can be covered by verification mission by the Commission under Article 35 of the Euratom Treaty. Currently, it is not included in the Commission verification mission planning for 2018-2020.',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 768]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities)
+# tensor([[1.0000, 0.7552, 0.6100],
+#         [0.7552, 1.0000, 0.5385],
+#         [0.6100, 0.5385, 1.0000]])
+```
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 59,612 training samples
+* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
+* Approximate statistics based on the first 100 samples:
+  |          | anchor                                                                              | positive                                                                             | negative                                                                             |
+  |:---------|:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type     | string                                                                              | string                                                                               | string                                                                               |
+  | modality | text                                                                                | text                                                                                 | text                                                                                 |
+  | details  | <ul><li>min: 29 tokens</li><li>mean: 235.8 tokens</li><li>max: 483 tokens</li></ul> | <ul><li>min: 37 tokens</li><li>mean: 327.66 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 94 tokens</li><li>mean: 392.99 tokens</li><li>max: 512 tokens</li></ul> |
+* Samples:
+  | anchor                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | positive                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    | negative                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
+  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>query: EU support for the Vál valley narrow-gauge railway<br>After a delay of several months, Prime Minister Viktor Orbán inaugurated the Vál valley narrow-gauge railway, co-financed by the EU, on 30 April 2016. In October 2013, by Order 1693/2013 (X.2.), the Hungarian Government had declared the narrow-gauge railway project a priority investment, and set aside EU development funding from the Central Transdanubia Operational Programme (KDOP-2.1.1.) for it. In the summer of 2015, a foundation belonging to the Mayor of Felcsút, Lőrinc Mészáros, the ‘Felcsúti Utánpótlás Nevelésért Alapítvány’, which is worth billions and which runs the football academy, secured non-refundable EU funding of HUF 600 million from the European Regional Development Fund. However, this sum was not enough to pay for the construction of the line, with its three stops, so the government contributed a further HUF 257 million. The narrow-gauge line, which is 5.7 km long, has been built in the village where the Prime Mi...</code>          | <code>passage: The Commission asked the Hungarian authorities to provide additional information on the project mentioned by the Honourable Member. On the basis of the information received, there is no evidence to prove the existence of irregularities in this project. It is necessary to underline that cohesion policy is implemented in the framework of the so-called shared management, whereby Member States are responsible for the selection of operations under an operational programme.<br>According to the information available to the Commission, data provided in the application and in the grant contract with the beneficiary of the project regarding amount expected of passengers do not correspond with those presented by the Honourable Member. The mandatory results to be achieved (including the passenger numbers) were agreed between the programme's managing authority and the beneficiary and are included in the grant contract. They will therefore be verified before carrying out the final payment to t...</code> | <code>passage: The state of development of the two core network corridors and the priorities for their further development are detailed in the Coordinators' work plans[1].<br>The two Spanish branches of the Mediterranean corridor are both integral parts of the Corridor and not variants; they have the same priority. Projects along the core network corridors receive EU co-funding once selected following a competitive tendering procedure open to all Member States. They are selected notably on the basis of their relevance for the corridor development and their maturity. Under the "use-it-or-lose-it" principle, EU funds, allocated to a specific project by a Member State, may be re-attributed to other projects if the funded project is severely delayed or not implemented.<br>The Commission is well aware of the technical and financial challenges arising from the different gauge used by the Spanish railway network. The Commission welcomes the policy of the Spanish authorities to implement the European gaug...</code>    |
+  | <code>query: Effectiveness of fines for breaking commercial laws<br>The EU is based on the rule of law. Imposing dissuasive sanctions for not complying with European law is justified. Yet it seems that sanctions are being imposed on large enterprises more and more often, which is worrying in terms of the rule of law.<br>In the case of Google, the regularity and severity of the fines imposed by the EU has raised doubts about their effectiveness in changing the behaviour of large enterprises. Nevertheless, the reports recently submitted by Google to the Commission have not resulted in more fines or sanctions, with the Commissioner concerned insisting that progress had been made. The severity of the sanctions imposed on Google may have persuaded other large enterprises not to break commercial laws. That being said, an exploratory survey has been initiated on commercial practices at Amazon.<br>I would therefore like to ask the Commission the following questions:<br>(1) Will the sanctions we have seen thus f...</code> | <code>passage: 1. The purpose of the fines imposed on undertakings for infringements of Article 101 or 102 of the Treaty on the Functioning of the European Union (TFEU) is two-fold. While fines are set in each individual case at a level that has a deterrent effect to sanction the undertaking concerned (specific deterrence), they are also aimed at deterring other undertakings from engaging in, or continuing, behaviour that is contrary to Articles 101 and 102 TFEU (general deterrence). The impact of the fine imposed in a specific case therefore is of broader relevance for the market as such.<br>As regards the fines imposed on Google during the last years, the cases concerned addressed different types of conduct. While the prohibition decision in Google Shopping of June 2017 dealt with Google's abuse of dominance in the market for general search which comprised Google treating more favourably its own comparison shopping service in its search results, the prohibition decision in Google Android of J...</code> | <code>passage: Under EU competition law, the Commission investigates and sanctions possible abuses of dominant position, including by companies in the digital sector. In its two decisions of 27 June 2017 and 18 July 2018, the Commission found that Google engaged in various abuses of dominant position and imposed fines of EUR 2.42 billion and EUR 4.34 billion[1].<br>The Commission also assesses if mergers by large IT players could strengthen the market position of the merging companies and harm consumers and small businesses. The Commission has for instance carefully investigated if Facebook’s purchase of Whatsapp could lead to competition concerns in consumer communications apps or strengthen Facebook's position in online advertising.<br>In the future, the Commission will continue to enforce competition law in the digital sector based on an analysis of the evidence in each case. Competition enforcement is complementary to data protection rules.<br>The Commission also seeks to set rules to protect bus...</code> |
+  | <code>query: The journalist Can Dündar and Turkish support for ISIS<br>The Cumhuriyet newspaper, a prominent supporter of Turkey’s opposition party, recently published evidence proving that the Turkish Government has supplied arms to Islamic terrorist groups in Syria. Photos show vast amounts of weapons crossing the Turkish border hidden in humanitarian aid convoys, escorted by the Turkish army and police. The government has reacted by threatening the journalist behind the exposé, Can Dündar, for which it has been quite rightly condemned by the international community. I have long accused Turkey of financing and supporting international Islamic terrorism, and the secret services of numerous countries have proved me right.<br>1. What further evidence does the Commission need for it to accept that Turkey is supporting terrorist barbarities?<br>2. Does the Commission not believe that the time has come to place Turkey on the list of ‘rogue’ states and to subject it to appropriate sanctions?<br>3. Does it no...</code> | <code>passage: The High Representative does not have evidence to support press allegations that Turkey has been assisting ISIL. The Turkish authorities have repeatedly dismissed such allegations. Turkey is a key partner in the coalition against ISIL, as recognised in the Foreign Affairs Council Conclusions of 9 February 2015. It is also providing outstanding humanitarian support to more than 2.5 million Syrian and Iraqi refugees fleeing violence across the border.<br>At the same time, the situation in Syria and Iraq to which the Honourable Member refers demands closer EU/Turkey foreign policy dialogue and cooperation. The Enlargement Strategy 2014-2015[1] highlights that Turkey has made clear its readiness to play an active role in the coalition against ISIL/Da'esh. The efforts to tackle ISIL/Da'esh should be further strengthened. Therefore we are expanding and intensifying our political dialogue with Turkey on foreign and security policy. The EU continues to encourage Turkey to develop its for...</code> | <code>passage: The Commission is following with concern the situation in regards to the freedom of expression and fundamental rights in Turkey. The Commission continues to closely monitor the situation of journalists in Turkey, including Can Dündar and Erdem Gül from the opposition daily newspaper, Cumhuriyet.<br>The EU is aware and has taken note of the request from the Director-General of Reporters Without Borders for the creation of a UN mechanism for protecting journalists.<br>The Commission has repeatedly called on Turkey to ensure that existing legislation complies with European standards and is implemented in a manner which ensures proportionality and equality before the law, in line with Article 10 of the European Convention for Human Rights[1] and the case-law of the European Court of Human Rights. Turkey, as any country negotiating EU membership, needs to ensure the respect of human rights, including freedom of expression. These are non-negotiable benchmarks for Turkish accession and a c...</code>    |
+* Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim",
+      "mini_batch_size": 8,
+      "mini_batch_num_tokens": null,
+      "gather_across_devices": false,
+      "directions": [
+          "query_to_doc"
+      ],
+      "partition_mode": "joint",
+      "hardness_mode": null,
+      "hardness_strength": 0.0
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `learning_rate`: 2e-05
+- `warmup_steps`: 0.1
+- `fp16`: True
+- `seed`: 15
+- `dataloader_num_workers`: 2
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `per_device_train_batch_size`: 32
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `learning_rate`: 2e-05
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: None
+- `warmup_steps`: 0.1
+- `optim`: adamw_torch_fused
+- `optim_args`: None
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `optim_target_modules`: None
+- `gradient_accumulation_steps`: 1
+- `average_tokens_across_devices`: True
+- `max_grad_norm`: 1.0
+- `label_smoothing_factor`: 0.0
+- `bf16`: False
+- `fp16`: True
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `use_liger_kernel`: False
+- `liger_kernel_config`: None
+- `use_cache`: False
+- `neftune_noise_alpha`: None
+- `torch_empty_cache_steps`: None
+- `auto_find_batch_size`: False
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `include_num_input_tokens_seen`: no
+- `log_level`: passive
+- `log_level_replica`: warning
+- `disable_tqdm`: False
+- `project`: huggingface
+- `trackio_space_id`: None
+- `trackio_bucket_id`: None
+- `trackio_static_space_id`: None
+- `per_device_eval_batch_size`: 8
+- `prediction_loss_only`: True
+- `eval_on_start`: False
+- `eval_do_concat_batches`: True
+- `eval_use_gather_object`: False
+- `eval_accumulation_steps`: None
+- `include_for_metrics`: []
+- `batch_eval_metrics`: False
+- `save_only_model`: False
+- `save_on_each_node`: False
+- `enable_jit_checkpoint`: False
+- `push_to_hub`: False
+- `hub_private_repo`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_always_push`: False
+- `hub_revision`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `restore_callback_states_from_checkpoint`: False
+- `full_determinism`: False
+- `seed`: 15
+- `data_seed`: None
+- `use_cpu`: False
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `parallelism_config`: None
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 2
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `dataloader_prefetch_factor`: None
+- `dataloader_multiprocessing_context`: None
+- `dataloader_in_order`: True
+- `remove_unused_columns`: True
+- `label_names`: None
+- `train_sampling_strategy`: random
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `ddp_static_graph`: None
+- `ddp_backend`: None
+- `ddp_timeout`: 1800
+- `fsdp`: None
+- `fsdp_config`: None
+- `deepspeed`: None
+- `debug`: []
+- `skip_memory_metrics`: True
+- `do_predict`: False
+- `resume_from_checkpoint`: None
+- `local_rank`: -1
+- `prompts`: None
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+- `router_mapping`: {}
+- `learning_rate_mapping`: {}
+- `warmup_ratio`: None
+
+</details>
+
+### Training Logs
+| Epoch  | Step | Training Loss |
+|:------:|:----:|:-------------:|
+| 0.0268 | 50   | 2.2394        |
+| 0.0537 | 100  | 0.6713        |
+| 0.0805 | 150  | 0.4274        |
+| 0.1074 | 200  | 0.3913        |
+| 0.1342 | 250  | 0.3676        |
+| 0.1610 | 300  | 0.3400        |
+| 0.1879 | 350  | 0.3518        |
+| 0.2147 | 400  | 0.3311        |
+| 0.2415 | 450  | 0.3545        |
+| 0.2684 | 500  | 0.3267        |
+| 0.2952 | 550  | 0.3253        |
+| 0.3221 | 600  | 0.3495        |
+| 0.3489 | 650  | 0.3104        |
+| 0.3757 | 700  | 0.3170        |
+| 0.4026 | 750  | 0.3122        |
+| 0.4294 | 800  | 0.3115        |
+| 0.4563 | 850  | 0.2795        |
+| 0.4831 | 900  | 0.2809        |
+| 0.5099 | 950  | 0.2867        |
+| 0.5368 | 1000 | 0.3012        |
+| 0.5636 | 1050 | 0.2657        |
+| 0.5904 | 1100 | 0.2778        |
+| 0.6173 | 1150 | 0.2811        |
+| 0.6441 | 1200 | 0.2919        |
+| 0.6710 | 1250 | 0.2686        |
+| 0.6978 | 1300 | 0.2649        |
+| 0.7246 | 1350 | 0.2599        |
+| 0.7515 | 1400 | 0.2616        |
+| 0.7783 | 1450 | 0.2710        |
+| 0.8052 | 1500 | 0.2566        |
+| 0.8320 | 1550 | 0.2414        |
+| 0.8588 | 1600 | 0.2438        |
+| 0.8857 | 1650 | 0.2673        |
+| 0.9125 | 1700 | 0.2625        |
+| 0.9393 | 1750 | 0.2457        |
+| 0.9662 | 1800 | 0.2556        |
+| 0.9930 | 1850 | 0.2477        |
+
+
+### Training Time
+- **Training**: 16.0 minutes
+
+### Framework Versions
+- Python: 3.14.4
+- Sentence Transformers: 6.1.0
+- Transformers: 5.20.2
+- PyTorch: 2.14.1+cu130
+- Accelerate: 1.15.0
+- Datasets: 5.1.0
+- Tokenizers: 0.23.3
+
+## Additional Resources
+
+- [Training and Finetuning Embedding Models with Sentence Transformers](https://huggingface.co/blog/train-sentence-transformers): the end-to-end guide for training or finetuning Sentence Transformer models.
+- [Introduction to Matryoshka Embedding Models](https://huggingface.co/blog/matryoshka): variable-size embeddings that can be truncated with minimal quality loss.
+- [Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval](https://huggingface.co/blog/embedding-quantization): post-training compression of embedding vectors.
+- [Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/multimodal-sentence-transformers): use text, image, audio, and video models through the same API.
+- [Training and Finetuning Multimodal Embedding & Reranker Models with Sentence Transformers](https://huggingface.co/blog/train-multimodal-sentence-transformers): train multimodal embedding models, with a Visual Document Retrieval walkthrough.
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### CachedMultipleNegativesRankingLoss
+```bibtex
+@misc{gao2021scaling,
+    title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
+    author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
+    year={2021},
+    eprint={2101.06983},
+    archivePrefix={arXiv},
+    primaryClass={cs.LG}
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{oord2019representationlearningcontrastivepredictive,
+      title={Representation Learning with Contrastive Predictive Coding},
+      author={Aaron van den Oord and Yazhe Li and Oriol Vinyals},
+      year={2019},
+      eprint={1807.03748},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/1807.03748},
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

v1.0/experiments/robustness/models/dm_s15/config.json

@@ -0,0 +1,30 @@
+{
+  "add_cross_attention": false,
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "is_decoder": false,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.20.2",
+  "type_vocab_size": 1,
+  "use_cache": false,
+  "vocab_size": 250002
+}

v1.0/experiments/robustness/models/dm_s15/config_sentence_transformers.json

@@ -0,0 +1,14 @@
+{
+  "__version__": {
+    "pytorch": "2.14.1+cu130",
+    "sentence_transformers": "6.1.0",
+    "transformers": "5.20.2"
+  },
+  "default_prompt_name": null,
+  "model_type": "SentenceTransformer",
+  "prompts": {
+    "document": "",
+    "query": ""
+  },
+  "similarity_fn_name": "cosine"
+}

v1.0/experiments/robustness/models/dm_s15/modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.base.modules.transformer.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.sentence_transformer.modules.pooling.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.base.modules.normalize.Normalize"
+  }
+]

v1.0/experiments/robustness/models/dm_s15/parlir_train_meta.json

@@ -0,0 +1,19 @@
+{
+ "base": "intfloat/multilingual-e5-base",
+ "n_pairs": 59612,
+ "epochs": 1,
+ "batch_size": 32,
+ "lr": 2e-05,
+ "max_len": 512,
+ "seed": 15,
+ "hard_negatives": true,
+ "min_year": 0,
+ "max_year": 0,
+ "hardneg_window_days": 365,
+ "negatives": "bm25",
+ "negative_stats": {
+  "date_matched_bm25": 58288,
+  "date_matched_random": 1324
+ },
+ "build": "data/build/v1.0"
+}

v1.0/experiments/robustness/models/dm_s15/sentence_bert_config.json

@@ -0,0 +1,10 @@
+{
+    "transformer_task": "feature-extraction",
+    "modality_config": {
+        "text": {
+            "method": "forward",
+            "method_output_name": "last_hidden_state"
+        }
+    },
+    "module_output_name": "token_embeddings"
+}

v1.0/experiments/robustness/models/dm_s15/tokenizer_config.json

@@ -0,0 +1,16 @@
+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "is_local": false,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}