Datasets:
Abzalbek89
/
kk-tokenizer-fertility-baseline

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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
morphbpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
bpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
unigram_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
unigram_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
bpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
bpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
morphbpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
morphbpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
unigram_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
vs
bpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
morphbpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
unigram_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
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 764, 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 6320, 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: 
              morphbpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              morphbpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              morphbpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              vs
              bpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
              morphbpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
              unigram_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: 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 1858, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, 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 6320, 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: 
              morphbpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed42: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              bpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              morphbpe_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              morphbpe_seed1: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              unigram_seed2: struct<test_loss: double, test_f1: double, test_precision: double, test_recall: double, test_accuracy: double, test_runtime: double, test_samples_per_second: double, test_steps_per_second: double, epoch: double, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string>
              vs
              bpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
              morphbpe_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: int64>
              unigram_seed42: struct<test_em: double, test_f1: double, n_test: int64, finetune_minutes: double, pretrained_model: string, dataset: string, seed: int64, epochs: int64, tag: string, max_len: 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 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 1869, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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tokenizer
string
vocab_size
int64
fertility
float64
chars_per_token
float64
bytes_per_token
float64
total_tokens
int64
total_words
int64
seconds
float64
kk-bpe-32k
32,000
1.6793
4.6724
8.4599
4,981,192
2,966,207
12.6
kk-unigram-32k
4
2
3.9232
7.1034
5,932,414
2,966,207
10.3
XLM-R
250,002
2.1811
3.5974
6.5136
6,469,672
2,966,207
16.4
GPT-4o (o200k)
200,019
2.5986
3.0196
5.4672
7,707,849
2,966,207
4.8
mBERT
119,547
2.9292
2.6787
4.8502
8,688,494
2,966,207
13
Qwen2.5
151,643
4.7862
1.6394
2.9683
14,196,803
2,966,207
17.3
Llama-3
128,000
4.8033
1.6336
2.9577
14,247,604
2,966,207
16
GPT-4 (cl100k)
100,277
5.8952
1.331
2.4099
17,486,314
2,966,207
3.5
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen2.5
null
null
null
null
null
null
null
XLM-R
null
null
null
null
null
null
null
mBERT
null
null
null
null
null
null
null
kk-morph-hf-unigram-32k
null
null
null
null
null
null
null
kk-morph-sp-unigram-32k
null
null
null
null
null
null
null
kk-hf-unigram-32k
null
null
null
null
null
null
null
kk-bpe-32k
null
null
null
null
null
null
null
kk-morph-hf-bpe-32k
null
null
null
null
null
null
null
kk-sp-unigram-32k
null
null
null
null
null
null
null
kk-sp-bpe-32k
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
null
kk-bpe-32k
32,000
1.6793
4.6724
8.4599
4,981,192
2,966,207
12.9
kk-sp-bpe-32k
32,000
1.758
4.4632
8.0812
5,214,647
2,966,207
11.2
kk-sp-unigram-32k
32,000
1.7617
4.454
8.0645
5,225,471
2,966,207
4.1
kk-hf-unigram-32k
32,000
2.0264
3.8722
7.011
6,010,620
2,966,207
23.8
XLM-R
250,002
2.1811
3.5974
6.5136
6,469,672
2,966,207
16.5
GPT-4o (o200k)
200,019
2.5986
3.0196
5.4672
7,707,849
2,966,207
4.9
mBERT
119,547
2.9292
2.6787
4.8502
8,688,494
2,966,207
13.4
Qwen2.5
151,643
4.7862
1.6394
2.9683
14,196,803
2,966,207
17.4
Llama-3
128,000
4.8033
1.6336
2.9577
14,247,604
2,966,207
16
GPT-4 (cl100k)
100,277
5.8952
1.331
2.4099
17,486,314
2,966,207
3.6
kk-bpe-32k
32,000
1.6793
4.6724
8.4599
4,981,192
2,966,207
12.9
kk-sp-bpe-32k
32,000
1.758
4.4632
8.0812
5,214,647
2,966,207
11.2
kk-morph-hf-bpe-32k
32,000
1.7608
4.4561
8.0682
5,223,030
2,966,207
62.7
kk-sp-unigram-32k
32,000
1.7617
4.454
8.0645
5,225,471
2,966,207
4.1
kk-morph-sp-unigram-32k
32,000
1.9449
4.0344
7.3048
5,768,923
2,966,207
8.5
kk-hf-unigram-32k
32,000
2.0264
3.8722
7.011
6,010,620
2,966,207
23.8
XLM-R
250,002
2.1811
3.5974
6.5136
6,469,672
2,966,207
16.5
kk-morph-hf-unigram-32k
32,000
2.3461
3.3445
6.0556
6,958,922
2,966,207
27
GPT-4o (o200k)
200,019
2.5986
3.0196
5.4672
7,707,849
2,966,207
4.9
mBERT
119,547
2.9292
2.6787
4.8502
8,688,494
2,966,207
13.4
Qwen2.5
151,643
4.7862
1.6394
2.9683
14,196,803
2,966,207
17.4
Llama-3
128,000
4.8033
1.6336
2.9577
14,247,604
2,966,207
16
GPT-4 (cl100k)
100,277
5.8952
1.331
2.4099
17,486,314
2,966,207
3.6