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w-ahmad
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benchio-results-expert

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The full dataset viewer is not available (click to read why). Only showing a preview of the rows.

The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'choice_logprob', 'all_logprobs'})

This happened while the csv dataset builder was generating data using

hf://datasets/w-ahmad/benchio-results-expert/results_expert_original/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv (at revision efb89908589d73b485219f18008510700efd0d0b), ['hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/benchmark_results_gsm8k_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/sample_statistics_gsm8k_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original_mmlu/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original_mmlu_exp/benchmark_results_mmlu_deepnevro_experts.csv']

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              original_idx: int64
              rollout_id: int64
              batch_size: int64
              level: string
              group: string
              input_tokens: int64
              input_chars: int64
              output_tokens: int64
              output_chars: int64
              correct: bool
              gt_answer: string
              model_answer: string
              generated_text: string
              choice_logprob: double
              all_logprobs: string
              idx: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2173
              to
              {'original_idx': Value('int64'), 'rollout_id': Value('int64'), 'batch_size': Value('int64'), 'level': Value('string'), 'group': Value('string'), 'input_tokens': Value('int64'), 'input_chars': Value('int64'), 'output_tokens': Value('int64'), 'output_chars': Value('int64'), 'correct': Value('bool'), 'gt_answer': Value('string'), 'model_answer': Value('float64'), 'generated_text': Value('string'), 'idx': Value('int64')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              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 1683, 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 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'choice_logprob', 'all_logprobs'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/w-ahmad/benchio-results-expert/results_expert_original/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv (at revision efb89908589d73b485219f18008510700efd0d0b), ['hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/benchmark_results_gsm8k_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original/sample_statistics_gsm8k_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original_mmlu/benchmark_results_mmlu_LiquidAI_LFM2.5-8B-A1B.csv', 'hf://datasets/w-ahmad/benchio-results-expert@efb89908589d73b485219f18008510700efd0d0b/results_expert_original_mmlu_exp/benchmark_results_mmlu_deepnevro_experts.csv']
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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original_idx int64	batch_size int64	level string	group string	input_tokens int64	input_chars int64	output_tokens int64	output_chars int64	correct bool	gt_answer string	model_answer null	generated_text string	idx int64
0	200	unknown	unknown	91	428	5	18	false	18	null	<think> We need to	0
1	200	unknown	unknown	56	253	5	18	false	3	null	<think> We need to	1
2	200	unknown	unknown	79	329	5	18	false	70000	null	<think> We need to	2
3	200	unknown	unknown	62	269	5	18	false	540	null	<think> We need to	3
4	200	unknown	unknown	135	619	5	18	false	20	null	<think> We need to	4
5	200	unknown	unknown	82	351	5	18	false	64	null	<think> We need to	5
6	200	unknown	unknown	69	335	5	18	false	260	null	<think> We need to	6
7	200	unknown	unknown	95	435	5	18	false	160	null	<think> We need to	7
8	200	unknown	unknown	130	554	5	18	false	45	null	<think> We need to	8
9	200	unknown	unknown	86	373	5	18	false	460	null	<think> We need to	9
10	200	unknown	unknown	90	416	5	18	false	366	null	<think> We need to	10
11	200	unknown	unknown	94	387	5	18	false	694	null	<think> We need to	11
12	200	unknown	unknown	95	404	5	18	false	13	null	<think> We need to	12
13	200	unknown	unknown	90	385	5	18	false	18	null	<think> We need to	13
14	200	unknown	unknown	77	367	5	18	false	60	null	<think> We need to	14
15	200	unknown	unknown	120	545	5	18	false	125	null	<think> We need to	15
16	200	unknown	unknown	78	370	5	18	false	230	null	<think> We need to	16
17	200	unknown	unknown	81	337	5	18	false	57500	null	<think> We need to	17
18	200	unknown	unknown	56	254	5	18	false	7	null	<think> We need to	18
19	200	unknown	unknown	92	403	5	18	false	6	null	<think> We need to	19
20	200	unknown	unknown	89	390	5	18	false	15	null	<think> We need to	20
21	200	unknown	unknown	75	325	5	18	false	14	null	<think> We need to	21
22	200	unknown	unknown	88	358	5	18	false	7	null	<think> We need to	22
23	200	unknown	unknown	65	290	5	18	false	8	null	<think> We need to	23
24	200	unknown	unknown	66	295	5	18	false	26	null	<think> We need to	24
25	200	unknown	unknown	92	378	5	18	false	2	null	<think> We need to	25
26	200	unknown	unknown	92	378	5	18	false	243	null	<think> We need to	26
27	200	unknown	unknown	86	355	5	18	false	16	null	<think> We need to	27
28	200	unknown	unknown	75	353	5	18	false	25	null	<think> We need to	28
29	200	unknown	unknown	95	459	5	18	false	104	null	<think> We need to	29
30	200	unknown	unknown	63	270	5	18	false	109	null	<think> We need to	30
31	200	unknown	unknown	88	385	5	18	false	80	null	<think> We need to	31
32	200	unknown	unknown	68	305	5	18	false	35	null	<think> We need to	32
33	200	unknown	unknown	57	259	5	18	false	70	null	<think> We need to	33
34	200	unknown	unknown	75	302	5	18	false	23	null	<think> We need to	34
35	200	unknown	unknown	78	321	5	18	false	9	null	<think> We need to	35
36	200	unknown	unknown	68	275	5	18	false	75	null	<think> We need to	36
37	200	unknown	unknown	88	370	5	18	false	2	null	<think> We need to	37
38	200	unknown	unknown	71	296	5	18	false	10	null	<think> We need to	38
39	200	unknown	unknown	101	449	5	18	false	18	null	<think> We need to	39
40	200	unknown	unknown	73	315	5	18	false	8	null	<think> We need to	40
41	200	unknown	unknown	159	693	5	18	false	200	null	<think> We need to	41
42	200	unknown	unknown	111	490	5	18	false	26	null	<think> We need to	42
43	200	unknown	unknown	81	366	5	18	false	48	null	<think> We need to	43
44	200	unknown	unknown	101	407	5	18	false	20	null	<think> We need to	44
45	200	unknown	unknown	125	591	5	18	false	104	null	<think> We need to	45
46	200	unknown	unknown	117	521	5	18	false	163	null	<think> We need to	46
47	200	unknown	unknown	75	317	5	18	false	800	null	<think> We need to	47
48	200	unknown	unknown	65	302	5	18	false	8	null	<think> We need to	48
49	200	unknown	unknown	70	329	5	18	false	30	null	<think> We need to	49
50	200	unknown	unknown	64	287	5	18	false	294	null	<think> We need to	50
51	200	unknown	unknown	76	304	5	18	false	5	null	<think> We need to	51
52	200	unknown	unknown	88	372	5	18	false	15	null	<think> We need to	52
53	200	unknown	unknown	125	585	5	18	false	40	null	<think> We need to	53
54	200	unknown	unknown	117	504	5	18	false	40	null	<think> We need to	54
55	200	unknown	unknown	77	305	5	18	false	14	null	<think> We need to	55
56	200	unknown	unknown	73	316	5	18	false	3	null	<think> We need to	56
57	200	unknown	unknown	100	485	5	18	false	83	null	<think> We need to	57
58	200	unknown	unknown	110	459	5	18	false	57	null	<think> We need to	58
59	200	unknown	unknown	60	285	5	18	false	187	null	<think> We need to	59
60	200	unknown	unknown	64	275	5	18	false	17	null	<think> We need to	60
61	200	unknown	unknown	86	359	5	18	false	1430	null	<think> We need to	61
62	200	unknown	unknown	92	393	5	18	false	25000	null	<think> We need to	62
63	200	unknown	unknown	95	465	5	18	false	1596	null	<think> We need to	63
64	200	unknown	unknown	119	521	5	18	false	300	null	<think> We need to	64
65	200	unknown	unknown	75	326	5	18	false	36	null	<think> We need to	65
66	200	unknown	unknown	86	421	5	18	false	48	null	<think> We need to	66
67	200	unknown	unknown	81	367	5	18	false	595	null	<think> We need to	67
68	200	unknown	unknown	64	292	5	18	false	36	null	<think> We need to	68
69	200	unknown	unknown	78	342	5	18	false	60	null	<think> We need to	69
70	200	unknown	unknown	79	338	5	18	false	7425	null	<think> We need to	70
71	200	unknown	unknown	71	364	5	18	false	60	null	<think> We need to	71
72	200	unknown	unknown	79	340	5	18	false	221	null	<think> We need to	72
73	200	unknown	unknown	73	314	5	18	false	255	null	<think> We need to	73
74	200	unknown	unknown	146	563	5	18	false	88	null	<think> We need to	74
75	200	unknown	unknown	95	445	5	18	false	60	null	<think> We need to	75
76	200	unknown	unknown	111	479	5	18	false	5	null	<think> We need to	76
77	200	unknown	unknown	71	351	5	18	false	100	null	<think> We need to	77
78	200	unknown	unknown	70	296	5	18	false	6	null	<think> We need to	78
79	200	unknown	unknown	75	317	5	18	false	70	null	<think> We need to	79
80	200	unknown	unknown	62	267	5	18	false	10	null	<think> We need to	80
81	200	unknown	unknown	84	390	5	18	false	17	null	<think> We need to	81
82	200	unknown	unknown	57	273	5	18	false	623	null	<think> We need to	82
83	200	unknown	unknown	59	259	5	18	false	600	null	<think> We need to	83
84	200	unknown	unknown	51	235	5	18	false	15	null	<think> We need to	84
85	200	unknown	unknown	113	495	5	18	false	44	null	<think> We need to	85
86	200	unknown	unknown	116	518	5	18	false	22	null	<think> We need to	86
87	200	unknown	unknown	104	494	5	18	false	9360	null	<think> We need to	87
88	200	unknown	unknown	61	282	5	18	false	8000	null	<think> We need to	88
89	200	unknown	unknown	76	341	5	18	false	24	null	<think> We need to	89
90	200	unknown	unknown	116	505	5	18	false	225	null	<think> We need to	90
91	200	unknown	unknown	68	297	5	18	false	28	null	<think> We need to	91
92	200	unknown	unknown	81	337	5	18	false	4	null	<think> We need to	92
93	200	unknown	unknown	110	457	5	18	false	36	null	<think> We need to	93
94	200	unknown	unknown	78	370	5	18	false	348	null	<think> We need to	94
95	200	unknown	unknown	68	279	5	18	false	40	null	<think> We need to	95
96	200	unknown	unknown	60	280	5	18	false	3	null	<think> We need to	96
97	200	unknown	unknown	81	383	5	18	false	12	null	<think> We need to	97
98	200	unknown	unknown	120	536	5	18	false	5	null	<think> We need to	98
99	200	unknown	unknown	112	504	5	18	false	58	null	<think> We need to	99

End of preview.

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