Add Matilda Jev v1.5 Decision Index 0.3 public run
Browse files- runs/matilda-jev-v1.5/RUN_NOTES.md +19 -0
- runs/matilda-jev-v1.5/benchmark-summary.json +1411 -0
- runs/matilda-jev-v1.5/environment.json +855 -0
- runs/matilda-jev-v1.5/index.json +497 -0
- runs/matilda-jev-v1.5/results.jsonl.gz +3 -0
- runs/matilda-jev-v1.5/scores.json +1420 -0
- runs/matilda-jev-v1.5/status.json +1 -0
runs/matilda-jev-v1.5/RUN_NOTES.md
ADDED
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# Matilda Jev v1.5: Decision Index 0.3 public suite
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- **Model:** [Maincode/matilda-jev-v1.5](https://huggingface.co/Maincode/matilda-jev-v1.5) @ `1b88863`. The weights used
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here are byte-identical to that commit: all 11 shards, `readout.safetensors` and `tokenizer.json` were checked by
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sha256. The stored temperature (1.5354) is the same.
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- **Kit:** apolinario/decision-index `62d2f51` (edition 0.3).
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- **Engine:** `kev.bench:KevEngine`, our in-process engine. Inference settings: bf16, one forward pass per question
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batch, the stored temperature, no thinking. The model repo ships its own engine,
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`maincode_jev_serve.engine:MaincodeJevEngine` in `runtime/`.
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- **Result:** `scores.json` is complete. Public index 63.47 (raw 72.62, breadth 62.45). 140,178 of 140,178 scored
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requests answered, all ok. Re-scoring `results.jsonl.gz` from scratch with the kit gives the same `scores.json`.
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- **Latency:** median 57 ms, mean 122 ms, p95 407 ms per request (1 × AMD MI355X per shard, in-process).
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## How the run was made
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One fresh run, no resume: 32 shards (4 nodes × 8 MI355X, one GPU per shard) over the union of the 0.3 and 0.2.1
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requests, 152,955 in all, every one answered ok. `scores.json` scores the 0.3 edition. The other 12,777 lines in
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`results.jsonl.gz` are requests that only 0.2.1 scores; 0.3 ignores them.
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The same results scored as 0.2.1 give 62.74, matching the 62.76 on the model card.
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runs/matilda-jev-v1.5/benchmark-summary.json
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|
| 1 |
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{
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| 2 |
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| 3 |
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| 4 |
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| 5 |
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| 7 |
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| 8 |
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| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 17 |
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| 23 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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{
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| 34 |
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| 35 |
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| 36 |
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| 49 |
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| 50 |
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| 51 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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{
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| 63 |
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| 64 |
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| 65 |
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| 66 |
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| 68 |
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| 81 |
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| 82 |
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| 83 |
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| 84 |
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| 85 |
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| 86 |
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| 101 |
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| 103 |
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| 104 |
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| 1333 |
+
"catalog_id": 59,
|
| 1334 |
+
"dataset": "RAGTruth response-level hallucination",
|
| 1335 |
+
"requests": 2700,
|
| 1336 |
+
"answered": 2700,
|
| 1337 |
+
"unsupported": 0,
|
| 1338 |
+
"errors": 0,
|
| 1339 |
+
"abstained": 0,
|
| 1340 |
+
"pending": 0,
|
| 1341 |
+
"metric": "F1 on hallucinated class",
|
| 1342 |
+
"score": 0.8415529905561385,
|
| 1343 |
+
"median_ms": 84.400126899709,
|
| 1344 |
+
"scored_requests": 2700,
|
| 1345 |
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"detail": {
|
| 1346 |
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"field_accuracy": 0.8881481481481481,
|
| 1347 |
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"scored_fields": 2700,
|
| 1348 |
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"chance_on_rows": 0.41125163541212384
|
| 1349 |
+
}
|
| 1350 |
+
},
|
| 1351 |
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{
|
| 1352 |
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"catalog_id": 61,
|
| 1353 |
+
"dataset": "HoVer claim verification",
|
| 1354 |
+
"requests": 4000,
|
| 1355 |
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"answered": 4000,
|
| 1356 |
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"unsupported": 0,
|
| 1357 |
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"errors": 0,
|
| 1358 |
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"abstained": 0,
|
| 1359 |
+
"pending": 0,
|
| 1360 |
+
"metric": "accuracy",
|
| 1361 |
+
"score": 0.86275,
|
| 1362 |
+
"median_ms": 61.5601270692423,
|
| 1363 |
+
"scored_requests": 4000,
|
| 1364 |
+
"detail": {
|
| 1365 |
+
"field_accuracy": 0.86275,
|
| 1366 |
+
"scored_fields": 4000,
|
| 1367 |
+
"chance_on_rows": 0.5
|
| 1368 |
+
}
|
| 1369 |
+
},
|
| 1370 |
+
{
|
| 1371 |
+
"catalog_id": 62,
|
| 1372 |
+
"dataset": "When2Call MCQ",
|
| 1373 |
+
"requests": 3652,
|
| 1374 |
+
"answered": 3652,
|
| 1375 |
+
"unsupported": 0,
|
| 1376 |
+
"errors": 0,
|
| 1377 |
+
"abstained": 0,
|
| 1378 |
+
"pending": 0,
|
| 1379 |
+
"metric": "accuracy",
|
| 1380 |
+
"score": 0.8619934282584885,
|
| 1381 |
+
"median_ms": 81.61521568399621,
|
| 1382 |
+
"scored_requests": 3652,
|
| 1383 |
+
"detail": {
|
| 1384 |
+
"field_accuracy": 0.8619934282584885,
|
| 1385 |
+
"scored_fields": 3652,
|
| 1386 |
+
"chance_on_rows": 0.25
|
| 1387 |
+
}
|
| 1388 |
+
},
|
| 1389 |
+
{
|
| 1390 |
+
"catalog_id": 64,
|
| 1391 |
+
"dataset": "New Yorker caption matching",
|
| 1392 |
+
"requests": 528,
|
| 1393 |
+
"answered": 528,
|
| 1394 |
+
"unsupported": 0,
|
| 1395 |
+
"errors": 0,
|
| 1396 |
+
"abstained": 0,
|
| 1397 |
+
"pending": 0,
|
| 1398 |
+
"metric": "accuracy",
|
| 1399 |
+
"score": 0.6912878787878788,
|
| 1400 |
+
"median_ms": 53.024440005174256,
|
| 1401 |
+
"scored_requests": 528,
|
| 1402 |
+
"detail": {
|
| 1403 |
+
"field_accuracy": 0.6912878787878788,
|
| 1404 |
+
"scored_fields": 528,
|
| 1405 |
+
"chance_on_rows": 0.2
|
| 1406 |
+
}
|
| 1407 |
+
}
|
| 1408 |
+
],
|
| 1409 |
+
"note": "Native benchmark metrics on complete supported case groups. Unsupported cases excluded from accuracy but retained in coverage.",
|
| 1410 |
+
"edition": "0.3"
|
| 1411 |
+
}
|
runs/matilda-jev-v1.5/environment.json
ADDED
|
@@ -0,0 +1,855 @@
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"runner_sha256": "f4c9f36c4c557f537f1d8184db7bf00c5a84d9f4f0aa67f8c06198cead25818d",
|
| 803 |
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"latency": "In-process request wall time: prompt rendering, tokenization and one forward pass per question batch."
|
| 804 |
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},
|
| 805 |
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{
|
| 806 |
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"engine": "kev.bench:KevEngine",
|
| 807 |
+
"engine_options": {
|
| 808 |
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"checkpoint": "/shared/model-cache/matilda-jev-scale50k-morecycles-di62p76"
|
| 809 |
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},
|
| 810 |
+
"model_source": {
|
| 811 |
+
"base_model": "/shared/model-cache/matilda-jev-v1-base",
|
| 812 |
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"revision": "unknown",
|
| 813 |
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"checkpoint": "/shared/model-cache/matilda-jev-scale50k-morecycles-di62p76",
|
| 814 |
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| 815 |
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|
| 817 |
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| 818 |
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|
| 819 |
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"device": "AMD Instinct MI355X",
|
| 820 |
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|
| 821 |
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| 822 |
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"hip": "7.2.53211",
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| 823 |
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"loaded_seconds": 82.36828273199717,
|
| 824 |
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"frozen_corpus_sha256": null,
|
| 825 |
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"rows_path": "/shared/training/arsh/data/decision-index/shards-32-0.3+0.2.1/shard-30.jsonl.gz",
|
| 826 |
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"runner_sha256": "f4c9f36c4c557f537f1d8184db7bf00c5a84d9f4f0aa67f8c06198cead25818d",
|
| 827 |
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"latency": "In-process request wall time: prompt rendering, tokenization and one forward pass per question batch."
|
| 828 |
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},
|
| 829 |
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{
|
| 830 |
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"engine": "kev.bench:KevEngine",
|
| 831 |
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"engine_options": {
|
| 832 |
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"checkpoint": "/shared/model-cache/matilda-jev-scale50k-morecycles-di62p76"
|
| 833 |
+
},
|
| 834 |
+
"model_source": {
|
| 835 |
+
"base_model": "/shared/model-cache/matilda-jev-v1-base",
|
| 836 |
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"revision": "unknown",
|
| 837 |
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"checkpoint": "/shared/model-cache/matilda-jev-scale50k-morecycles-di62p76",
|
| 838 |
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"checkpoint_config_sha256": "64f86b3afe31f5863ecd3637295ec23fb31bc65630964093ce8ed9cdb84a5171",
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| 839 |
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"temperature": 1.5353518467887404,
|
| 840 |
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|
| 841 |
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|
| 842 |
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},
|
| 843 |
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"device": "AMD Instinct MI355X",
|
| 844 |
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"memory_gib": 288,
|
| 845 |
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|
| 846 |
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|
| 847 |
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|
| 848 |
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|
| 849 |
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"rows_path": "/shared/training/arsh/data/decision-index/shards-32-0.3+0.2.1/shard-31.jsonl.gz",
|
| 850 |
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"runner_sha256": "f4c9f36c4c557f537f1d8184db7bf00c5a84d9f4f0aa67f8c06198cead25818d",
|
| 851 |
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"latency": "In-process request wall time: prompt rendering, tokenization and one forward pass per question batch."
|
| 852 |
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}
|
| 853 |
+
]
|
| 854 |
+
}
|
| 855 |
+
}
|
runs/matilda-jev-v1.5/index.json
ADDED
|
@@ -0,0 +1,497 @@
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"edition": "0.3",
|
| 3 |
+
"panel_id": "decision-index-0.3",
|
| 4 |
+
"index": 63.47,
|
| 5 |
+
"raw_index": 72.62,
|
| 6 |
+
"scores": {
|
| 7 |
+
"balanced_skill": 63.47,
|
| 8 |
+
"balanced_raw": 72.62,
|
| 9 |
+
"breadth_skill": 62.45
|
| 10 |
+
},
|
| 11 |
+
"areas": [
|
| 12 |
+
{
|
| 13 |
+
"id": "knowledge",
|
| 14 |
+
"label": "Knowledge & Reasoning",
|
| 15 |
+
"raw": 0.6093,
|
| 16 |
+
"skill": 0.4983,
|
| 17 |
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"coverage": 1.0,
|
| 18 |
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"n": 11,
|
| 19 |
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"benchmarks": [
|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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|
| 25 |
+
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|
| 26 |
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44,
|
| 27 |
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45,
|
| 28 |
+
57,
|
| 29 |
+
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|
| 30 |
+
28
|
| 31 |
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]
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"id": "language",
|
| 35 |
+
"label": "Language Understanding",
|
| 36 |
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"raw": 0.7852,
|
| 37 |
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"skill": 0.6991,
|
| 38 |
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"coverage": 1.0,
|
| 39 |
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"n": 9,
|
| 40 |
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|
| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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|
| 46 |
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|
| 47 |
+
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|
| 48 |
+
42,
|
| 49 |
+
59
|
| 50 |
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]
|
| 51 |
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},
|
| 52 |
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{
|
| 53 |
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"id": "retrieval",
|
| 54 |
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"label": "Retrieval & Classification",
|
| 55 |
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"raw": 0.7498,
|
| 56 |
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"skill": 0.6596,
|
| 57 |
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"coverage": 1.0,
|
| 58 |
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"n": 6,
|
| 59 |
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"benchmarks": [
|
| 60 |
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|
| 61 |
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5,
|
| 62 |
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|
| 63 |
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37,
|
| 64 |
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56,
|
| 65 |
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61
|
| 66 |
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]
|
| 67 |
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},
|
| 68 |
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{
|
| 69 |
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"id": "tools",
|
| 70 |
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"label": "Tools & Automation",
|
| 71 |
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"raw": 0.8296,
|
| 72 |
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"skill": 0.8084,
|
| 73 |
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"coverage": 1.0,
|
| 74 |
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"n": 5,
|
| 75 |
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|
| 76 |
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1,
|
| 77 |
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2,
|
| 78 |
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3,
|
| 79 |
+
9,
|
| 80 |
+
62
|
| 81 |
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]
|
| 82 |
+
},
|
| 83 |
+
{
|
| 84 |
+
"id": "arts",
|
| 85 |
+
"label": "Arts & Human Taste",
|
| 86 |
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"raw": 0.6399,
|
| 87 |
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"skill": 0.4541,
|
| 88 |
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"coverage": 1.0,
|
| 89 |
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"n": 6,
|
| 90 |
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"benchmarks": [
|
| 91 |
+
20,
|
| 92 |
+
21,
|
| 93 |
+
22,
|
| 94 |
+
23,
|
| 95 |
+
50,
|
| 96 |
+
64
|
| 97 |
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]
|
| 98 |
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}
|
| 99 |
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],
|
| 100 |
+
"benchmarks": {
|
| 101 |
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"1": {
|
| 102 |
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"raw": 0.9664,
|
| 103 |
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"skill": 0.9546,
|
| 104 |
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"coverage": 1.0,
|
| 105 |
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"random": 0.2592,
|
| 106 |
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"rule": "track",
|
| 107 |
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"in_index": true,
|
| 108 |
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"tracks": []
|
| 109 |
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},
|
| 110 |
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"2": {
|
| 111 |
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"raw": 0.6743,
|
| 112 |
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"skill": 0.6238,
|
| 113 |
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"coverage": 1.0,
|
| 114 |
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"random": 0.1341,
|
| 115 |
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"rule": "track",
|
| 116 |
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"in_index": true,
|
| 117 |
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"tracks": []
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|
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|
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|
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|
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|
| 493 |
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}
|
| 494 |
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},
|
| 495 |
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"coverage": 1.0,
|
| 496 |
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"note": "The Decision Index 0.3 public index averages 37 benchmarks in five areas with fixed weights (knowledge 25.8%, language 25.8%, retrieval 20.0%, tools 18.3%, arts 10%). Inside an area, gold ★ benchmarks weigh 1.2 and the rest 1.0; the index is 100 x the weighted mean of the five areas. Each benchmark is chance-corrected first, (score - chance) / (1 - chance) clipped to 0-1, so 0 means random guessing and 100 means perfect. Every score is coverage-adjusted, so an unanswered or unsupported request counts as wrong. On the board this public index is 20% of the Full score; the rest comes from private tests run by the maintainers."
|
| 497 |
+
}
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runs/matilda-jev-v1.5/scores.json
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|
| 1 |
+
{
|
| 2 |
+
"engine": "matilda-jev-scale50k-morecycles-di62p76",
|
| 3 |
+
"edition": "0.3",
|
| 4 |
+
"generated_utc": "2026-10-08T23:46:23+00:00",
|
| 5 |
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"suite": {
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| 6 |
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"edition": "release-v3",
|
| 7 |
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"requests": 110201,
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| 8 |
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| 9 |
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|
| 10 |
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|
| 11 |
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| 12 |
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|
| 13 |
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"added_sha256": "7429f3c9cdddb772c1cfc42bb2a45e8516b0032152b746e6929f1c8b52f4ce89",
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| 14 |
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|
| 15 |
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},
|
| 16 |
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"completed": 140178,
|
| 17 |
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"complete": true,
|
| 18 |
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"counts": {
|
| 19 |
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"ok": 140178
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| 20 |
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},
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| 21 |
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| 22 |
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"median": 57.3,
|
| 23 |
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|
| 24 |
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| 25 |
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},
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| 26 |
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|
| 27 |
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| 28 |
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|
| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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| 37 |
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| 38 |
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| 39 |
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| 40 |
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| 41 |
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| 42 |
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| 45 |
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| 47 |
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| 49 |
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| 50 |
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| 51 |
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| 52 |
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| 53 |
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| 54 |
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| 55 |
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{
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| 56 |
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"id": "language",
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 70 |
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| 71 |
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| 72 |
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| 73 |
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| 74 |
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{
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| 75 |
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"id": "retrieval",
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| 76 |
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| 77 |
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| 88 |
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| 89 |
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| 90 |
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| 91 |
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| 92 |
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| 93 |
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| 94 |
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| 103 |
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| 104 |
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| 105 |
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| 106 |
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| 107 |
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"note": "The Decision Index 0.3 public index averages 37 benchmarks in five areas with fixed weights (knowledge 25.8%, language 25.8%, retrieval 20.0%, tools 18.3%, arts 10%). Inside an area, gold ★ benchmarks weigh 1.2 and the rest 1.0; the index is 100 x the weighted mean of the five areas. Each benchmark is chance-corrected first, (score - chance) / (1 - chance) clipped to 0-1, so 0 means random guessing and 100 means perfect. Every score is coverage-adjusted, so an unanswered or unsupported request counts as wrong. On the board this public index is 20% of the Full score; the rest comes from private tests run by the maintainers."
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| 1420 |
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}
|
runs/matilda-jev-v1.5/status.json
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{"time": "2026-10-08T23:46:01.378569+00:00", "event": "complete", "completed": 152955, "counts": {"ok": 152955}, "shards": 32}
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