Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
engine: string
model: string
organization: string
model_repository: string
checkpoint: string
declared_limits: struct<max_state_length: int64, max_option_length: int64>
torch: string
device: string
cuda: string
gpu: string
allocated_mb: double
latency: string
median_latency_ms: double
vs
edition: string
panel_id: string
index: double
balanced_raw: double
unweighted_raw: double
coverage: double
n_requests: int64
n_scored: int64
areas: list<item: struct<id: string, label: string, raw: double, skill: double, coverage: double, n: int64, benchmarks: list<item: int64>>>
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 783, in write_table
self.write_rows_on_file() # in case there are buffered rows to write first
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
table = pa.concat_tables(self.current_rows)
File "pyarrow/table.pxi", line 6268, in pyarrow.lib.concat_tables
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: Schema at index 1 was different:
engine: string
model: string
organization: string
model_repository: string
checkpoint: string
declared_limits: struct<max_state_length: int64, max_option_length: int64>
torch: string
device: string
cuda: string
gpu: string
allocated_mb: double
latency: string
median_latency_ms: double
vs
edition: string
panel_id: string
index: double
balanced_raw: double
unweighted_raw: double
coverage: double
n_requests: int64
n_scored: int64
areas: list<item: struct<id: string, label: string, raw: double, skill: double, coverage: double, n: int64, benchmarks: list<item: int64>>>
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 1868, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 803, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
table = pa.concat_tables(self.current_rows)
File "pyarrow/table.pxi", line 6268, in pyarrow.lib.concat_tables
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: Schema at index 1 was different:
engine: string
model: string
organization: string
model_repository: string
checkpoint: string
declared_limits: struct<max_state_length: int64, max_option_length: int64>
torch: string
device: string
cuda: string
gpu: string
allocated_mb: double
latency: string
median_latency_ms: double
vs
edition: string
panel_id: string
index: double
balanced_raw: double
unweighted_raw: double
coverage: double
n_requests: int64
n_scored: int64
areas: list<item: struct<id: string, label: string, raw: double, skill: double, coverage: double, n: int64, benchmarks: list<item: int64>>>
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 1369, 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 948, 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 1694, 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 1879, 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.
catalog_id int64 | dataset string | requests int64 | answered int64 | unsupported int64 | errors int64 | abstained int64 | pending int64 | scored_requests int64 | metric string | score float64 | median_ms float64 | index_raw float64 | index_skill float64 | coverage float64 | chance float64 | in_index bool |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | catalog_1 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 1 | 32.48 | 1 | 1 | 1 | 0.2592 | true |
2 | catalog_2 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.7175 | 1,238.79 | 0.7175 | 0.6737 | 1 | 0.1341 | true |
3 | catalog_3 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8971 | 17.8 | 0.8971 | 0.8951 | 1 | 0.0189 | true |
4 | catalog_4 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9574 | 19.28 | 0.9574 | 0.9569 | 1 | 0.0127 | true |
5 | catalog_5 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9824 | 23.33 | 0.9824 | 0.9823 | 1 | 0.006 | true |
9 | catalog_9 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9446 | 825.05 | 0.9446 | 0.9446 | 1 | 0 | true |
11 | catalog_11 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8951 | 1,357.85 | 0.8951 | 0.8483 | 1 | 0.3085 | true |
12 | catalog_12 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8145 | 30.89 | 0.8145 | 0.7222 | 1 | 0.3324 | true |
20 | catalog_20 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9792 | 30.72 | 0.9792 | 0.9583 | 1 | 0.5 | true |
21 | catalog_21 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6397 | 31.5 | 0.6397 | 0.2795 | 1 | 0.5 | true |
22 | catalog_22 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.5385 | 63.43 | 0.5385 | 0.5349 | 1 | 0.0078 | true |
23 | catalog_23 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.7357 | 34.12 | 0.7357 | 0.4713 | 1 | 0.5 | true |
25 | catalog_25 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.5382 | 15.49 | 0.5382 | 0.3843 | 1 | 0.25 | true |
28 | catalog_28 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9616 | 30.97 | 0.9616 | 0.9231 | 1 | 0.5 | true |
29 | catalog_29 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 1 | 15.77 | 1 | 1 | 1 | 0.25 | true |
30 | catalog_30 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6849 | 15.73 | 0.6849 | 0.6181 | 1 | 0.175 | true |
31 | catalog_31 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.2019 | 17.13 | 0.2019 | 0.1307 | 1 | 0.0819 | true |
32 | catalog_32 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6946 | 72.02 | 0.6946 | 0.5144 | 1 | 0.371 | true |
33 | catalog_33 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.1741 | 130.32 | 0.1741 | 0.1632 | 1 | 0.0131 | true |
36 | catalog_36 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.5367 | 1,081.77 | 0.5367 | 0.4759 | 1 | 0.116 | true |
37 | catalog_37 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6445 | 16.86 | 0.6445 | 0.5542 | 1 | 0.2027 | true |
38 | catalog_38 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6086 | 1,994.46 | 0.6086 | 0.5961 | 1 | 0.031 | true |
39 | catalog_39 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.964 | 62.79 | 0.964 | 0.947 | 1 | 0.3201 | true |
40 | catalog_40 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.5246 | 31.13 | 0.5246 | 0.3884 | 1 | 0.2227 | true |
41 | catalog_41 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8474 | 31.42 | 0.8474 | 0.7712 | 1 | 0.3333 | true |
42 | catalog_42 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8836 | 35.15 | 0.8836 | 0.7734 | 1 | 0.486 | true |
43 | catalog_43 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.811 | 30.01 | 0.811 | 0.7002 | 1 | 0.3697 | true |
44 | catalog_44 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.7621 | 30.6 | 0.7621 | 0.5243 | 1 | 0.5 | true |
45 | catalog_45 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.1808 | 16.15 | 0.1808 | 0.02 | 1 | 0.1641 | true |
50 | catalog_50 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.6252 | 18.14 | 0.6252 | 0.456 | 1 | 0.311 | true |
56 | catalog_56 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.7196 | 283.46 | 0.7196 | 0.4392 | 1 | 0.5 | true |
57 | catalog_57 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.7395 | 15.84 | 0.7395 | 0.707 | 1 | 0.1109 | true |
58 | catalog_58 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8359 | 31.14 | 0.8359 | 0.7621 | 1 | 0.3101 | true |
59 | catalog_59 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8799 | 44.41 | 0.8799 | 0.751 | 1 | 0.5177 | true |
61 | catalog_61 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.916 | 32.02 | 0.916 | 0.8321 | 1 | 0.5 | true |
62 | catalog_62 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.9238 | 40.63 | 0.9238 | 0.8984 | 1 | 0.25 | true |
64 | catalog_64 | 25 | 25 | 0 | 0 | 0 | 0 | 25 | accuracy | 0.8235 | 15.62 | 0.8235 | 0.7793 | 1 | 0.2 | true |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | 1 | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
1 | BFCL | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
2 | ToolRet | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
3 | API-Bank | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
End of preview.
Decision Index Official Evaluation: DM-JEPA 1.1 (Danger Labs)
Official evaluation run artifacts and scorecard for DM-JEPA 1.1 (Decision-Making Joint Embedding Predictive Architecture), developed by Danger Labs, evaluated across the complete 150,759-request suite of the Decision Index (v0.2.1 protocol).
Executive Scorecard
| Metric | Score | Notes |
|---|---|---|
| Decision Index (Balanced Skill) | 23.16 | Full 44-benchmark panel (+26.1% over v1.0) |
| Raw Index (Balanced Raw) | 41.92 | Full panel |
| Breadth Skill | 22.40 | Geometric mean across all 5 areas |
| Total Requests Evaluated | 150,759 | Full-panel evaluation |
| Requests Answered (ok) | 150,518 (99.84%) | 7,207 requests recovered via context stretch |
| Unsupported (Capacity Limit) | 241 (0.16%) | Exceeding 16k context / 512 option ceiling |
| Completion Flag | true |
Verified in runs/dm-jepa/scores.json |
| Median Forward Latency | 34.3 ms | Device-synchronized System 1 forward pass |
| Model Repository | DangerLabs/DM-JEPA |
Architecture & checkpoints |
5-Area Breakdown (Decision Index 0.2.1)
| Area | Balanced Skill | Balanced Raw | Coverage |
|---|---|---|---|
| Tools & Automation | 31.90% | 42.11% | 95.63% |
| Retrieval & Classification | 28.23% | 42.58% | 100.00% |
| Knowledge & Reasoning | 25.26% | 43.71% | 99.92% |
| Arts & Human Taste | 16.73% | 38.67% | 100.00% |
| Language Understanding | 13.44% | 40.81% | 100.00% |
Key Benchmark Highlights
- GSM8K (Arithmetic Reasoning): 100.00% Raw / 100.00% Skill
- Home Appliance Simulator: 91.12% Field Accuracy / 82.25% Field Skill
- OpenJev High-Trust Suite: 100.00% Accuracy (0.0000 Brier)
- Jevbench-Hard: 85.59% Accuracy (92.45% trap avoidance)
- Long-Context Recovery: 7,207 previously unsupported requests answered through 16,384-token context expansion.
- Inference Speed: 34.3 ms median per request (System 1 non-autoregressive forward pass).
Repository Files
All files in runs/dm-jepa/ adhere to the Decision Index submission specification:
runs/
└── dm-jepa/
├── scores.json # Combined scorecard ("complete": true, 23.16 Balanced Skill)
├── benchmark-summary.json # Native per-benchmark metrics for all 44 datasets
├── index.json # Decision Index 0.2.1 calculation breakdown & areas
├── environment.json # Hardware, runtime environment, declared capacity limits
├── status.json # Final completed run status event
└── results.jsonl.gz # Gzipped evaluation log (43.4 MB, 150,759 rows)
Re-Scoring & Verification
To re-score this run using the Decision Index kit:
git clone https://github.com/apolinario/decision-index.git
cd decision-index
python -m decision_index score --edition 0.2.1 --results runs/dm-jepa/results.jsonl.gz
Published by Danger Labs · Hugging Face Organization
- Downloads last month
- 175