Reorder default data splits to have validation before test
_The documentation is not available anymore as the PR was closed or merged._ After this CI error: https://github.com/huggingface/datasets/actions/runs/4639528358/jobs/8210492953?pr=5718
```
FAILED tests/test_data_files.py::test_get_data_files_patterns[data_file_per_split4] - AssertionError: assert ['random', 'train'] == ['train', 'random']
  At index 0 diff: 'random' != 'train'
  Full diff:
  - ['train', 'random']
  + ['random', 'train']
```
I have checked locally and found out that the data split order is nondeterministic. I am addressing this in a separate issue.

We should first address:
- #5728 
- #5729 <details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.007728 / 0.011353 (-0.003624) | 0.005275 / 0.011008 (-0.005734) | 0.097708 / 0.038508 (0.059199) | 0.039851 / 0.023109 (0.016741) | 0.333360 / 0.275898 (0.057462) | 0.376135 / 0.323480 (0.052655) | 0.006355 / 0.007986 (-0.001630) | 0.004193 / 0.004328 (-0.000135) | 0.072882 / 0.004250 (0.068631) | 0.052668 / 0.037052 (0.015615) | 0.347359 / 0.258489 (0.088870) | 0.382280 / 0.293841 (0.088440) | 0.035996 / 0.128546 (-0.092550) | 0.012517 / 0.075646 (-0.063129) | 0.334520 / 0.419271 (-0.084751) | 0.051969 / 0.043533 (0.008436) | 0.335735 / 0.255139 (0.080596) | 0.359921 / 0.283200 (0.076722) | 0.113971 / 0.141683 (-0.027712) | 1.465636 / 1.452155 (0.013481) | 1.559824 / 1.492716 (0.067108) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.223997 / 0.018006 (0.205991) | 0.499041 / 0.000490 (0.498551) | 0.009697 / 0.000200 (0.009497) | 0.000245 / 0.000054 (0.000190) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.027031 / 0.037411 (-0.010381) | 0.110271 / 0.014526 (0.095745) | 0.115848 / 0.176557 (-0.060709) | 0.174253 / 0.737135 (-0.562883) | 0.122616 / 0.296338 (-0.173723) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.417275 / 0.215209 (0.202066) | 4.158678 / 2.077655 (2.081023) | 1.917585 / 1.504120 (0.413465) | 1.722219 / 1.541195 (0.181025) | 1.813284 / 1.468490 (0.344793) | 0.707193 / 4.584777 (-3.877584) | 3.853545 / 3.745712 (0.107833) | 3.369240 / 5.269862 (-1.900621) | 1.820264 / 4.565676 (-2.745412) | 0.087340 / 0.424275 (-0.336936) | 0.012305 / 0.007607 (0.004698) | 0.520326 / 0.226044 (0.294281) | 5.107383 / 2.268929 (2.838455) | 2.413977 / 55.444624 (-53.030647) | 2.074356 / 6.876477 (-4.802121) | 2.255959 / 2.142072 (0.113887) | 0.849850 / 4.805227 (-3.955377) | 0.170116 / 6.500664 (-6.330548) | 0.067203 / 0.075469 (-0.008267) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.168158 / 1.841788 (-0.673629) | 15.046312 / 8.074308 (6.972004) | 15.113924 / 10.191392 (4.922532) | 0.145288 / 0.680424 (-0.535136) | 0.017959 / 0.534201 (-0.516242) | 0.424666 / 0.579283 (-0.154617) | 0.422560 / 0.434364 (-0.011804) | 0.526386 / 0.540337 (-0.013952) | 0.623755 / 1.386936 (-0.763181) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.007676 / 0.011353 (-0.003677) | 0.005240 / 0.011008 (-0.005769) | 0.074668 / 0.038508 (0.036160) | 0.035570 / 0.023109 (0.012461) | 0.348524 / 0.275898 (0.072626) | 0.378157 / 0.323480 (0.054677) | 0.006112 / 0.007986 (-0.001873) | 0.005641 / 0.004328 (0.001312) | 0.073536 / 0.004250 (0.069286) | 0.048651 / 0.037052 (0.011599) | 0.359282 / 0.258489 (0.100793) | 0.385961 / 0.293841 (0.092120) | 0.035417 / 0.128546 (-0.093129) | 0.012227 / 0.075646 (-0.063419) | 0.085725 / 0.419271 (-0.333546) | 0.049651 / 0.043533 (0.006118) | 0.344122 / 0.255139 (0.088983) | 0.364795 / 0.283200 (0.081595) | 0.112711 / 0.141683 (-0.028972) | 1.426823 / 1.452155 (-0.025332) | 1.534745 / 1.492716 (0.042029) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.201728 / 0.018006 (0.183721) | 0.448533 / 0.000490 (0.448043) | 0.003554 / 0.000200 (0.003354) | 0.000092 / 0.000054 (0.000038) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.030917 / 0.037411 (-0.006494) | 0.117966 / 0.014526 (0.103440) | 0.125954 / 0.176557 (-0.050602) | 0.176382 / 0.737135 (-0.560753) | 0.130757 / 0.296338 (-0.165582) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.422167 / 0.215209 (0.206958) | 4.213948 / 2.077655 (2.136294) | 2.040049 / 1.504120 (0.535929) | 1.858317 / 1.541195 (0.317122) | 1.937108 / 1.468490 (0.468618) | 0.707797 / 4.584777 (-3.876979) | 3.831061 / 3.745712 (0.085349) | 3.373711 / 5.269862 (-1.896151) | 1.590343 / 4.565676 (-2.975333) | 0.086672 / 0.424275 (-0.337603) | 0.012429 / 0.007607 (0.004821) | 0.520269 / 0.226044 (0.294225) | 5.207285 / 2.268929 (2.938357) | 2.518107 / 55.444624 (-52.926517) | 2.230696 / 6.876477 (-4.645781) | 2.363164 / 2.142072 (0.221091) | 0.836749 / 4.805227 (-3.968479) | 0.169676 / 6.500664 (-6.330988) | 0.065766 / 0.075469 (-0.009703) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.251195 / 1.841788 (-0.590592) | 15.196091 / 8.074308 (7.121782) | 14.991600 / 10.191392 (4.800208) | 0.165335 / 0.680424 (-0.515089) | 0.017789 / 0.534201 (-0.516412) | 0.433863 / 0.579283 (-0.145420) | 0.428660 / 0.434364 (-0.005704) | 0.527385 / 0.540337 (-0.012952) | 0.628067 / 1.386936 (-0.758869) |

</details>
</details>

![](https://cml.dev/watermark.png#d06b8c21ba98ae85971a2b1d135ac2ef035b59c9 "CML watermark")

This PR reorders data splits, so that by default validation appears before test.

The default order becomes: [train, validation, test] instead of [train, test, validation].