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The dataset generation failed
Error code: DatasetGenerationError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 306, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
task string | instance_id int64 | rollout_id int64 | steps int64 | success bool | agent_distance dict | normalized_agent_distance dict | q_score dict | time dict |
|---|---|---|---|---|---|---|---|---|
assembling_gift_baskets | 301 | 0 | 39,091 | false | {
"base": 114.42387648731918,
"left": 188.59040572044125,
"right": 202.8307520828775
} | {
"base": 0.6966054852094923,
"left": 0.21342602157431653,
"right": 0.1902798249460224
} | {
"final": 0.625
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 302 | 0 | 39,091 | false | {
"base": 107.64020036569045,
"left": 174.7880283069933,
"right": 183.22637205570018
} | {
"base": 0.7405067969885204,
"left": 0.23027950134723035,
"right": 0.21063889202732985
} | {
"final": 0.875
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 303 | 0 | 39,091 | false | {
"base": 101.15201307047312,
"left": 167.51113581438474,
"right": 174.467331541933
} | {
"base": 0.7880050784996916,
"left": 0.24028312986069308,
"right": 0.22121390668902297
} | {
"final": 0.625
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 304 | 0 | 26,494 | true | {
"base": 85.60904011645752,
"left": 132.2022085222943,
"right": 134.71644052771262
} | {
"base": 0.9310733993929787,
"left": 0.30445860511636086,
"right": 0.28648767625404026
} | {
"final": 1
} | {
"simulator_steps": 26494,
"simulator_time": 883.1333333333333,
"normalized_time": 0.9836210085302333
} |
assembling_gift_baskets | 305 | 0 | 39,091 | false | {
"base": 147.53740473497143,
"left": 221.07721118066792,
"right": 229.10837886684865
} | {
"base": 0.5402582493787516,
"left": 0.1820635414434777,
"right": 0.16845564614828032
} | {
"final": 0.75
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 306 | 0 | 39,091 | false | {
"base": 139.72392573366687,
"left": 207.36507217101462,
"right": 220.98944707442934
} | {
"base": 0.5704699433648539,
"left": 0.194102601651283,
"right": 0.17464453851048065
} | {
"final": 0.75
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 307 | 0 | 23,338 | true | {
"base": 79.57795154092452,
"left": 126.14154678542991,
"right": 127.81260256022233
} | {
"base": 1.0016379971656904,
"left": 0.3190867800952725,
"right": 0.30196239828396515
} | {
"final": 1
} | {
"simulator_steps": 23338,
"simulator_time": 777.9333333333333,
"normalized_time": 1.116636172765447
} |
assembling_gift_baskets | 308 | 0 | 39,091 | false | {
"base": 63.71187063531917,
"left": 149.96995629284484,
"right": 149.75891673343511
} | {
"base": 1.2510745518090796,
"left": 0.2683877557542528,
"right": 0.257711532921254
} | {
"final": 0.6875
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 309 | 0 | 39,091 | false | {
"base": 139.17722270859855,
"left": 245.53945620209134,
"right": 259.2404364437856
} | {
"base": 0.5727108103521275,
"left": 0.1639251818122141,
"right": 0.148875694430367
} | {
"final": 0.6875
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
assembling_gift_baskets | 310 | 0 | 39,091 | false | {
"base": 136.75680592277735,
"left": 198.59205411921465,
"right": 212.60794127591384
} | {
"base": 0.5828470434225335,
"left": 0.2026772933011605,
"right": 0.18152943755714898
} | {
"final": 0.5
} | {
"simulator_steps": 39091,
"simulator_time": 1303.0333333333333,
"normalized_time": 0.666651019416234
} |
attach_a_camera_to_a_tripod | 301 | 0 | 5,868 | false | {
"base": 5.519832374836049,
"left": 13.78156021842824,
"right": 14.981861944459524
} | {
"base": 2.0478158089602747,
"left": 0.5746374049442127,
"right": 0.3890704654474296
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 302 | 0 | 5,868 | false | {
"base": 3.892573251915188,
"left": 12.057740046315303,
"right": 10.361837065402142
} | {
"base": 2.903888833546936,
"left": 0.6567897441461322,
"right": 0.5625450355191217
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 303 | 0 | 5,868 | false | {
"base": 10.888567317182897,
"left": 15.87070515479354,
"right": 18.38675595987843
} | {
"base": 1.0381163720374997,
"left": 0.49899484129777616,
"right": 0.31702166563364453
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 304 | 0 | 4,485 | true | {
"base": 5.0405270888506095,
"left": 12.19267021253836,
"right": 12.459780620733
} | {
"base": 2.2425432500904496,
"left": 0.6495213814490011,
"right": 0.4678252512970075
} | {
"final": 1
} | {
"simulator_steps": 4485,
"simulator_time": 149.5,
"normalized_time": 0.8721460423634336
} |
attach_a_camera_to_a_tripod | 305 | 0 | 5,868 | false | {
"base": 2.7727509822477785,
"left": 15.152934690616163,
"right": 10.98646969024351
} | {
"base": 4.076673337191117,
"left": 0.5226314348800228,
"right": 0.5305616967365249
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 306 | 0 | 5,868 | false | {
"base": 4.9059939873425265,
"left": 13.80648353077595,
"right": 14.588646052571676
} | {
"base": 2.3040386982053604,
"left": 0.573600075815606,
"right": 0.3995572981203741
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 307 | 0 | 5,868 | false | {
"base": 4.454068527260134,
"left": 14.30122465471868,
"right": 13.879554983370326
} | {
"base": 2.5378145690437486,
"left": 0.5537567719689656,
"right": 0.41997023730112154
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 308 | 0 | 5,868 | false | {
"base": 5.054186122843376,
"left": 15.048160719010411,
"right": 12.94245693222365
} | {
"base": 2.2364827343637352,
"left": 0.5262702962758355,
"right": 0.4503781647120781
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 309 | 0 | 5,868 | false | {
"base": 6.146450535068581,
"left": 12.76413251548911,
"right": 12.677068781155867
} | {
"base": 1.8390451424781336,
"left": 0.6204416939725368,
"right": 0.4598066083434568
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
attach_a_camera_to_a_tripod | 310 | 0 | 5,868 | false | {
"base": 7.178764849594799,
"left": 16.492998908557638,
"right": 16.613029473883216
} | {
"base": 1.5745884197109512,
"left": 0.4801673754971815,
"right": 0.35086917826538344
} | {
"final": 0
} | {
"simulator_steps": 5868,
"simulator_time": 195.6,
"normalized_time": 0.666594239945467
} |
boxing_books_up_for_storage | 301 | 0 | 36,342 | false | {
"base": 43.699203204952525,
"left": 87.20820565947457,
"right": 96.5621118772342
} | {
"base": 1.6538058980400239,
"left": 0.2987184497491122,
"right": 0.25341719981343164
} | {
"final": 0.8333333333333334
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 302 | 0 | 36,342 | false | {
"base": 41.29226843580663,
"left": 88.28530611377028,
"right": 90.17976216548686
} | {
"base": 1.750206581950121,
"left": 0.2950740179393992,
"right": 0.2713524566087759
} | {
"final": 0.5
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 303 | 0 | 36,342 | false | {
"base": 50.00129208012534,
"left": 98.64148420684614,
"right": 102.49077654788925
} | {
"base": 1.445362649512933,
"left": 0.2640947691477656,
"right": 0.23875806998658122
} | {
"final": 0.5
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 304 | 0 | 36,342 | false | {
"base": 40.09209374590626,
"left": 83.65132973729533,
"right": 98.97380360831221
} | {
"base": 1.8025997958108477,
"left": 0.31142003458655704,
"right": 0.2472421904369943
} | {
"final": 0.6666666666666666
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 305 | 0 | 36,342 | false | {
"base": 44.261752905248414,
"left": 78.45067198234301,
"right": 92.64214687091498
} | {
"base": 1.6327866669607307,
"left": 0.33206471457457065,
"right": 0.26414003589636714
} | {
"final": 0.8333333333333334
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 306 | 0 | 36,342 | false | {
"base": 46.152415121935235,
"left": 83.28452967130988,
"right": 88.60465199257851
} | {
"base": 1.5658985517672648,
"left": 0.312791584497283,
"right": 0.2761762441327532
} | {
"final": 0.16666666666666666
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 307 | 0 | 36,342 | false | {
"base": 48.16604525766553,
"left": 91.85558076736379,
"right": 101.97634633769576
} | {
"base": 1.5004345823575451,
"left": 0.28360497840601306,
"right": 0.23996250972716437
} | {
"final": 0.6666666666666666
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 308 | 0 | 36,342 | false | {
"base": 33.331239975236244,
"left": 77.19024575066078,
"right": 87.79934737806235
} | {
"base": 2.1682361668420875,
"left": 0.33748694212153085,
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} | {
"final": 0.3333333333333333
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 309 | 0 | 36,342 | false | {
"base": 35.40972100914847,
"left": 80.4594794449049,
"right": 78.76642702280287
} | {
"base": 2.0409649649972756,
"left": 0.32377415538511367,
"right": 0.31067170271562267
} | {
"final": 0.3333333333333333
} | {
"simulator_steps": 36342,
"simulator_time": 1211.4,
"normalized_time": 0.6666529084805459
} |
boxing_books_up_for_storage | 310 | 0 | 24,877 | true | {
"base": 31.388938100902493,
"left": 75.84963614460321,
"right": 79.40606127542378
} | {
"base": 2.302403469900184,
"left": 0.34345187827052664,
"right": 0.30816917004764766
} | {
"final": 1
} | {
"simulator_steps": 24877,
"simulator_time": 829.2333333333333,
"normalized_time": 0.973891546408329
} |
boxing_food_after_dinner | 301 | 0 | 10,047 | false | {
"base": 28.53454098683703,
"left": 55.816836970807344,
"right": 54.79284884533263
} | {
"base": 0.5646069445249497,
"left": 0.19998625156488406,
"right": 0.32305310588916036
} | {
"final": 0.6666666666666666
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 302 | 0 | 10,047 | false | {
"base": 28.734717640469952,
"left": 47.55765050655282,
"right": 58.75537967765922
} | {
"base": 0.5606736840632658,
"left": 0.23471723016388163,
"right": 0.30126603039773253
} | {
"final": 0.16666666666666666
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 303 | 0 | 10,047 | false | {
"base": 29.818927494805912,
"left": 52.07983934334624,
"right": 55.552483642270545
} | {
"base": 0.540287708295555,
"left": 0.2143362986665231,
"right": 0.31863561877782726
} | {
"final": 0.3333333333333333
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 304 | 0 | 4,899 | true | {
"base": 14.885937069264962,
"left": 25.26962664142775,
"right": 29.748337737131806
} | {
"base": 1.0822832264462556,
"left": 0.44173980717624506,
"right": 0.5950248432841225
} | {
"final": 1
} | {
"simulator_steps": 4899,
"simulator_time": 163.3,
"normalized_time": 1.3671596244131456
} |
boxing_food_after_dinner | 305 | 0 | 10,047 | false | {
"base": 35.189508242416125,
"left": 57.54210113172118,
"right": 62.76975571877901
} | {
"base": 0.4578296431144963,
"left": 0.1939901355782506,
"right": 0.2819988670866269
} | {
"final": 0.16666666666666666
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 306 | 0 | 10,047 | false | {
"base": 34.935534481921806,
"left": 53.991329539074826,
"right": 65.95235827612278
} | {
"base": 0.4611579653471998,
"left": 0.20674801112132934,
"right": 0.2683907059985818
} | {
"final": 0.3333333333333333
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 307 | 0 | 4,424 | true | {
"base": 12.678665954435289,
"left": 23.770836264504396,
"right": 24.46778492334124
} | {
"base": 1.2707015121227383,
"left": 0.4695922295619216,
"right": 0.7234410493413316
} | {
"final": 1
} | {
"simulator_steps": 4424,
"simulator_time": 147.46666666666667,
"normalized_time": 1.5139500452079566
} |
boxing_food_after_dinner | 308 | 0 | 7,618 | true | {
"base": 25.202076092778718,
"left": 36.119488379616996,
"right": 52.31874687349409
} | {
"base": 0.6392647947212695,
"left": 0.3090464594260226,
"right": 0.3383299688503767
} | {
"final": 1
} | {
"simulator_steps": 7618,
"simulator_time": 253.93333333333334,
"normalized_time": 0.8791959831976897
} |
boxing_food_after_dinner | 309 | 0 | 10,047 | false | {
"base": 37.42060243958599,
"left": 55.70405232154907,
"right": 68.53522454596904
} | {
"base": 0.43053288695739783,
"left": 0.20039116607826674,
"right": 0.2582759466721715
} | {
"final": 0.3333333333333333
} | {
"simulator_steps": 10047,
"simulator_time": 334.9,
"normalized_time": 0.6666382999900468
} |
boxing_food_after_dinner | 310 | 0 | 4,803 | true | {
"base": 12.929952324872211,
"left": 24.22879943047883,
"right": 25.35011802133522
} | {
"base": 1.2460061410287704,
"left": 0.46071618331851427,
"right": 0.6982610489269694
} | {
"final": 1
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canning_food | 308 | 0 | 34,464 | false | {
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canning_food | 309 | 0 | 34,464 | false | {
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canning_food | 310 | 0 | 34,464 | false | {
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carrying_in_groceries | 301 | 0 | 10,971 | true | {
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carrying_in_groceries | 302 | 0 | 12,593 | true | {
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carrying_in_groceries | 303 | 0 | 11,207 | true | {
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carrying_in_groceries | 304 | 0 | 21,413 | false | {
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carrying_in_groceries | 305 | 0 | 21,413 | false | {
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} | {
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carrying_in_groceries | 306 | 0 | 14,665 | true | {
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} | {
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} | {
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carrying_in_groceries | 307 | 0 | 13,142 | true | {
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} | {
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} | {
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carrying_in_groceries | 308 | 0 | 10,785 | true | {
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"left": 69.88679472817239,
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} | {
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} | {
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} | {
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carrying_in_groceries | 309 | 0 | 21,413 | false | {
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} | {
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} | {
"final": 0.25
} | {
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} |
carrying_in_groceries | 310 | 0 | 21,413 | false | {
"base": 60.90227440063675,
"left": 83.11616704337757,
"right": 91.39606809622819
} | {
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} | {
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} | {
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} |
End of preview.
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Check out the documentation for more information.
BEHAVIOR 2026 Self-Evaluation
This dataset contains three independent evaluation rounds: round0/, round1/, and round2/. Each round covers 100 tasks with instances 301-310, totaling 1,000 episodes. Results are reported separately for each round.
Files are named {task}_{instance}_{rollout}.
| Directory | Successful episodes | Macro Q-score | Video size |
|---|---|---|---|
round0/ |
398 | 0.604701 | 29.50 GB |
round1/ |
416 | 0.617207 | 29.32 GB |
round2/ |
414 | 0.618579 | 29.06 GB |
Each round contains metrics/, videos/, robot/r1pro.yaml, wrapper/default_wrapper.py, and selection_index.json.
Macro Q-score is calculated by averaging the 10 instance Q-scores within each task, then averaging the 100 task means equally.
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