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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 19 new columns ({'train/cls_loss', 'lr/pg6', 'val/box_loss', 'lr/pg2', 'time', 'lr/pg3', 'lr/pg4', 'val/cls_loss', 'lr/pg0', 'metrics/precision(B)', 'train/box_loss', 'lr/pg7', 'metrics/mAP50(B)', 'lr/pg1', 'metrics/mAP50-95(B)', 'val/dfl_loss', 'metrics/recall(B)', 'lr/pg5', 'train/dfl_loss'}) and 7 missing columns ({'det_accuracy', 'mAP50-95', 'f1', 'recall', 'mAP50', 'fitness', 'precision'}).
This happened while the csv dataset builder was generating data using
hf://datasets/TamAko783/n-rdd2024-augmented/runs/yolo26_distilled_frdc/results.csv (at revision 9203f30bc281d52a63e67ad266c005af6ceadcac), ['hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26_distilled_frdc/metrics_distill.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26_distilled_frdc/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_fresh_gcp/metrics_full.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_fresh_gcp/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_nomosaic_ft/metrics_finetune.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_nomosaic_ft/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_p2_v2/metrics_v2.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_p2_v2/results.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/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/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/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
epoch: int64
time: double
train/box_loss: double
train/cls_loss: double
train/dfl_loss: double
metrics/precision(B): double
metrics/recall(B): double
metrics/mAP50(B): double
metrics/mAP50-95(B): double
val/box_loss: double
val/cls_loss: double
val/dfl_loss: double
lr/pg0: double
lr/pg1: double
lr/pg2: double
lr/pg3: double
lr/pg4: double
lr/pg5: double
lr/pg6: double
lr/pg7: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2691
to
{'epoch': Value('int64'), 'precision': Value('float64'), 'recall': Value('float64'), 'f1': Value('float64'), 'det_accuracy': Value('float64'), 'mAP50': Value('float64'), 'mAP50-95': Value('float64'), 'fitness': Value('float64')}
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 1343, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
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 19 new columns ({'train/cls_loss', 'lr/pg6', 'val/box_loss', 'lr/pg2', 'time', 'lr/pg3', 'lr/pg4', 'val/cls_loss', 'lr/pg0', 'metrics/precision(B)', 'train/box_loss', 'lr/pg7', 'metrics/mAP50(B)', 'lr/pg1', 'metrics/mAP50-95(B)', 'val/dfl_loss', 'metrics/recall(B)', 'lr/pg5', 'train/dfl_loss'}) and 7 missing columns ({'det_accuracy', 'mAP50-95', 'f1', 'recall', 'mAP50', 'fitness', 'precision'}).
This happened while the csv dataset builder was generating data using
hf://datasets/TamAko783/n-rdd2024-augmented/runs/yolo26_distilled_frdc/results.csv (at revision 9203f30bc281d52a63e67ad266c005af6ceadcac), ['hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26_distilled_frdc/metrics_distill.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26_distilled_frdc/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_fresh_gcp/metrics_full.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_fresh_gcp/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_nomosaic_ft/metrics_finetune.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_nomosaic_ft/results.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_p2_v2/metrics_v2.csv', 'hf://datasets/TamAko783/n-rdd2024-augmented@9203f30bc281d52a63e67ad266c005af6ceadcac/runs/yolo26n_p2_v2/results.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)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
epoch int64 | precision float64 | recall float64 | f1 float64 | det_accuracy float64 | mAP50 float64 | mAP50-95 float64 | fitness float64 |
|---|---|---|---|---|---|---|---|
1 | 0.4638 | 0.4169 | 0.4391 | 0.2814 | 0.4327 | 0.2238 | 0.2447 |
2 | 0.4524 | 0.4083 | 0.4292 | 0.2733 | 0.42 | 0.2154 | 0.2359 |
3 | 0.4182 | 0.3714 | 0.3934 | 0.2449 | 0.3669 | 0.1751 | 0.1943 |
4 | 0.4168 | 0.3738 | 0.3941 | 0.2454 | 0.3683 | 0.1781 | 0.1971 |
5 | 0.428 | 0.3993 | 0.4131 | 0.2604 | 0.395 | 0.1948 | 0.2148 |
6 | 0.4525 | 0.397 | 0.4229 | 0.2682 | 0.4042 | 0.2012 | 0.2215 |
7 | 0.4538 | 0.4005 | 0.4255 | 0.2703 | 0.4029 | 0.2016 | 0.2217 |
8 | 0.4458 | 0.4103 | 0.4273 | 0.2717 | 0.4158 | 0.2078 | 0.2286 |
9 | 0.4607 | 0.4138 | 0.436 | 0.2788 | 0.4227 | 0.2137 | 0.2346 |
10 | 0.458 | 0.411 | 0.4333 | 0.2765 | 0.4255 | 0.218 | 0.2387 |
11 | 0.4537 | 0.4272 | 0.4401 | 0.2821 | 0.4293 | 0.2207 | 0.2415 |
12 | 0.4592 | 0.4267 | 0.4423 | 0.284 | 0.4301 | 0.221 | 0.2419 |
13 | 0.4711 | 0.4167 | 0.4422 | 0.2839 | 0.433 | 0.2223 | 0.2434 |
14 | 0.464 | 0.4211 | 0.4415 | 0.2833 | 0.4361 | 0.2256 | 0.2466 |
15 | 0.4693 | 0.4192 | 0.4429 | 0.2844 | 0.4371 | 0.2274 | 0.2484 |
16 | 0.4614 | 0.4263 | 0.4431 | 0.2846 | 0.4374 | 0.2289 | 0.2497 |
17 | 0.4645 | 0.4298 | 0.4465 | 0.2874 | 0.4376 | 0.2293 | 0.2501 |
18 | 0.4686 | 0.4259 | 0.4462 | 0.2872 | 0.4384 | 0.2306 | 0.2513 |
19 | 0.4686 | 0.4273 | 0.447 | 0.2878 | 0.4396 | 0.2313 | 0.2521 |
20 | 0.4733 | 0.4267 | 0.4488 | 0.2893 | 0.4408 | 0.2316 | 0.2525 |
21 | 0.4756 | 0.4267 | 0.4498 | 0.2902 | 0.4408 | 0.2314 | 0.2523 |
22 | 0.4773 | 0.4218 | 0.4478 | 0.2885 | 0.4409 | 0.2319 | 0.2528 |
23 | 0.4776 | 0.4244 | 0.4494 | 0.2899 | 0.4414 | 0.2322 | 0.2531 |
24 | 0.4761 | 0.4267 | 0.45 | 0.2903 | 0.4423 | 0.2324 | 0.2534 |
25 | 0.4727 | 0.4293 | 0.4499 | 0.2903 | 0.442 | 0.2323 | 0.2533 |
26 | 0.4752 | 0.427 | 0.4498 | 0.2902 | 0.442 | 0.2321 | 0.2531 |
27 | 0.4755 | 0.4286 | 0.4509 | 0.291 | 0.4423 | 0.2326 | 0.2535 |
28 | 0.4721 | 0.431 | 0.4506 | 0.2908 | 0.4431 | 0.2332 | 0.2542 |
29 | 0.4693 | 0.4343 | 0.4511 | 0.2912 | 0.4436 | 0.2338 | 0.2547 |
30 | 0.4733 | 0.4289 | 0.45 | 0.2903 | 0.4438 | 0.234 | 0.255 |
31 | 0.4728 | 0.4285 | 0.4496 | 0.29 | 0.4431 | 0.2339 | 0.2548 |
32 | 0.471 | 0.4314 | 0.4503 | 0.2906 | 0.4431 | 0.2339 | 0.2549 |
33 | 0.4697 | 0.4335 | 0.4509 | 0.291 | 0.4444 | 0.2347 | 0.2557 |
34 | 0.4704 | 0.4359 | 0.4525 | 0.2924 | 0.4451 | 0.2353 | 0.2562 |
35 | 0.4701 | 0.4358 | 0.4523 | 0.2922 | 0.4452 | 0.235 | 0.256 |
36 | 0.4655 | 0.4357 | 0.4501 | 0.2904 | 0.4446 | 0.2348 | 0.2558 |
37 | 0.4689 | 0.4316 | 0.4495 | 0.2899 | 0.4442 | 0.2348 | 0.2557 |
38 | 0.4686 | 0.4324 | 0.4498 | 0.2901 | 0.4433 | 0.2339 | 0.2549 |
39 | 0.4709 | 0.4331 | 0.4512 | 0.2913 | 0.4442 | 0.2348 | 0.2557 |
40 | 0.4773 | 0.4295 | 0.4521 | 0.2921 | 0.4441 | 0.2355 | 0.2563 |
41 | 0.4806 | 0.4253 | 0.4513 | 0.2914 | 0.4441 | 0.2361 | 0.2569 |
42 | 0.4766 | 0.4306 | 0.4524 | 0.2924 | 0.4447 | 0.2359 | 0.2568 |
43 | 0.4736 | 0.4289 | 0.4501 | 0.2904 | 0.4449 | 0.2356 | 0.2566 |
44 | 0.4844 | 0.4229 | 0.4516 | 0.2916 | 0.4464 | 0.2364 | 0.2574 |
45 | 0.4845 | 0.4234 | 0.4519 | 0.2919 | 0.4456 | 0.2367 | 0.2576 |
46 | 0.4834 | 0.4247 | 0.4522 | 0.2921 | 0.4464 | 0.237 | 0.2579 |
47 | 0.4828 | 0.4238 | 0.4514 | 0.2915 | 0.4461 | 0.2372 | 0.2581 |
48 | 0.4845 | 0.4234 | 0.4519 | 0.2919 | 0.4471 | 0.2372 | 0.2582 |
49 | 0.4822 | 0.4245 | 0.4515 | 0.2916 | 0.4473 | 0.2374 | 0.2584 |
50 | 0.4786 | 0.4298 | 0.4529 | 0.2927 | 0.4478 | 0.2382 | 0.2592 |
51 | 0.4802 | 0.4259 | 0.4514 | 0.2915 | 0.4477 | 0.2384 | 0.2593 |
52 | 0.4768 | 0.4292 | 0.4517 | 0.2918 | 0.4488 | 0.2389 | 0.2599 |
53 | 0.4781 | 0.4289 | 0.4522 | 0.2921 | 0.4493 | 0.2392 | 0.2602 |
54 | 0.477 | 0.4302 | 0.4524 | 0.2923 | 0.4496 | 0.2391 | 0.2602 |
55 | 0.4801 | 0.4296 | 0.4535 | 0.2932 | 0.4504 | 0.2394 | 0.2605 |
56 | 0.477 | 0.4289 | 0.4516 | 0.2917 | 0.45 | 0.2391 | 0.2602 |
57 | 0.4812 | 0.4276 | 0.4528 | 0.2927 | 0.4496 | 0.2388 | 0.2599 |
58 | 0.49 | 0.4244 | 0.4549 | 0.2944 | 0.4505 | 0.2395 | 0.2606 |
59 | 0.4907 | 0.4246 | 0.4552 | 0.2947 | 0.4512 | 0.2402 | 0.2613 |
60 | 0.4911 | 0.4248 | 0.4555 | 0.2949 | 0.4513 | 0.2401 | 0.2612 |
61 | 0.4907 | 0.426 | 0.4561 | 0.2954 | 0.451 | 0.2401 | 0.2612 |
62 | 0.4948 | 0.4233 | 0.4562 | 0.2955 | 0.4511 | 0.2404 | 0.2614 |
63 | 0.4848 | 0.4311 | 0.4564 | 0.2957 | 0.4512 | 0.2407 | 0.2617 |
64 | 0.4912 | 0.4265 | 0.4566 | 0.2958 | 0.4506 | 0.2409 | 0.2619 |
65 | 0.4849 | 0.4306 | 0.4562 | 0.2955 | 0.4514 | 0.2414 | 0.2624 |
66 | 0.4857 | 0.4283 | 0.4552 | 0.2947 | 0.4514 | 0.2413 | 0.2623 |
67 | 0.489 | 0.428 | 0.4564 | 0.2957 | 0.4512 | 0.2414 | 0.2624 |
68 | 0.4842 | 0.4317 | 0.4564 | 0.2957 | 0.4505 | 0.2412 | 0.2621 |
69 | 0.4829 | 0.4326 | 0.4564 | 0.2956 | 0.451 | 0.2422 | 0.2631 |
70 | 0.4814 | 0.435 | 0.457 | 0.2962 | 0.4511 | 0.2416 | 0.2626 |
71 | 0.4813 | 0.4331 | 0.4559 | 0.2953 | 0.4509 | 0.2419 | 0.2628 |
72 | 0.4825 | 0.4323 | 0.456 | 0.2953 | 0.4506 | 0.2418 | 0.2627 |
73 | 0.4835 | 0.4336 | 0.4572 | 0.2963 | 0.4511 | 0.2421 | 0.263 |
74 | 0.4984 | 0.4224 | 0.4572 | 0.2964 | 0.4508 | 0.2418 | 0.2627 |
75 | 0.4915 | 0.4285 | 0.4578 | 0.2969 | 0.4516 | 0.2423 | 0.2633 |
76 | 0.4909 | 0.4273 | 0.4569 | 0.2961 | 0.4519 | 0.243 | 0.2639 |
77 | 0.4906 | 0.4249 | 0.4554 | 0.2949 | 0.4521 | 0.2431 | 0.264 |
78 | 0.4889 | 0.4267 | 0.4557 | 0.295 | 0.4514 | 0.2426 | 0.2635 |
79 | 0.4926 | 0.4244 | 0.4559 | 0.2953 | 0.4507 | 0.242 | 0.2629 |
80 | 0.4964 | 0.4231 | 0.4568 | 0.296 | 0.4513 | 0.2423 | 0.2632 |
81 | 0.493 | 0.4264 | 0.4573 | 0.2964 | 0.4509 | 0.2424 | 0.2632 |
82 | 0.4993 | 0.4197 | 0.4561 | 0.2954 | 0.4513 | 0.2427 | 0.2635 |
83 | 0.4987 | 0.422 | 0.4572 | 0.2963 | 0.4522 | 0.2431 | 0.264 |
84 | 0.4961 | 0.424 | 0.4572 | 0.2964 | 0.4527 | 0.2432 | 0.2641 |
85 | 0.5067 | 0.4172 | 0.4576 | 0.2967 | 0.4532 | 0.2434 | 0.2644 |
86 | 0.5102 | 0.4145 | 0.4574 | 0.2965 | 0.4531 | 0.2435 | 0.2644 |
87 | 0.5116 | 0.4151 | 0.4583 | 0.2973 | 0.4532 | 0.2433 | 0.2643 |
88 | 0.5046 | 0.422 | 0.4596 | 0.2984 | 0.4526 | 0.2429 | 0.2639 |
89 | 0.5033 | 0.422 | 0.4591 | 0.2979 | 0.4545 | 0.2437 | 0.2648 |
90 | 0.5035 | 0.4213 | 0.4587 | 0.2976 | 0.4545 | 0.2437 | 0.2648 |
91 | 0.5064 | 0.4205 | 0.4595 | 0.2982 | 0.4544 | 0.2434 | 0.2645 |
92 | 0.5065 | 0.4199 | 0.4591 | 0.298 | 0.4547 | 0.2444 | 0.2654 |
93 | 0.5029 | 0.4231 | 0.4596 | 0.2983 | 0.4548 | 0.2443 | 0.2654 |
94 | 0.4962 | 0.4247 | 0.4577 | 0.2968 | 0.4549 | 0.2444 | 0.2655 |
95 | 0.502 | 0.423 | 0.4591 | 0.298 | 0.4548 | 0.2444 | 0.2655 |
96 | 0.4994 | 0.4234 | 0.4582 | 0.2972 | 0.4548 | 0.2445 | 0.2655 |
97 | 0.5071 | 0.4176 | 0.458 | 0.297 | 0.4543 | 0.2447 | 0.2656 |
98 | 0.502 | 0.421 | 0.4579 | 0.297 | 0.4544 | 0.2447 | 0.2656 |
99 | 0.4968 | 0.4225 | 0.4567 | 0.2959 | 0.4541 | 0.2446 | 0.2656 |
100 | 0.4986 | 0.4225 | 0.4574 | 0.2965 | 0.454 | 0.2445 | 0.2654 |
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