Dataset Viewer
The dataset viewer is not available for this split.
The info cannot be fetched for the config 'default' of the dataset.
Error code: InfoError
Exception: ReadTimeout
Message: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 80db7c6d-f74e-4f3c-b6bf-afc44e188672)')
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 208, in compute_first_rows_from_streaming_response
info = get_dataset_config_info(path=dataset, config_name=config, token=hf_token)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1132, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 591, in get_module
standalone_yaml_path = cached_path(
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 169, in cached_path
).resolve_path(url_or_filename)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
self._api.repo_info(
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2816, in repo_info
return method(
^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/hf_api.py", line 2673, in dataset_info
r = get_session().get(path, headers=headers, timeout=timeout, params=params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 602, in get
return self.request("GET", url, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 589, in request
resp = self.send(prep, **send_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/sessions.py", line 703, in send
r = adapter.send(request, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/huggingface_hub/utils/_http.py", line 96, in send
return super().send(request, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/requests/adapters.py", line 690, in send
raise ReadTimeout(e, request=request)
requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 80db7c6d-f74e-4f3c-b6bf-afc44e188672)')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.
Dataset Card for carps
This dataset contains several optimizer runs on a subselection of blackbox tasks (test subset). The entries already are normalized.
Repo: https://github.com/automl/CARP-S/tree/main/carps Paper: https://arxiv.org/abs/2506.06143
Dataset Structure
# Identifying information of the run
optimizer_id: The identifier of the optimizer.
task_id: The identifier of the task.
seed: Which seed has been used. The combination of a unique `optimizer_id`, `task_id`, `seed`, equals one optimization run.
experiment_id: Experiment id. Enumeration of all runs.
# Information about the progress of the optimization
n_trials: The number of trials that have been evaluated so far.
n_function_calls: The number of times the objective function has been called. This can differ from `n_trials`, when we are in the multi-fidelity settings and can call the objective function with a lower fidelity. This still results in a full increase of `n_function_calls`, but only a fractional increase in `n_trials`.
n_trials_norm: The number of trials, normalized per run.
time: The elapsed time.
time_norm: The elapsed time, normalized per run.
# Information about the trial (ask)
trial_info__config: The configuration that has been evaluated.
trial_info__instance: The instance that the configuration has been evaluated on (None for anything but Algorithm Configuration).
trial_info__seed: The seed with which the objective function has been evaluated. In case of stochastic objective functions, we might wish to evaluate the objective function several times with different seeds for the same configuration.
trial_info__budget: The multi-fidelity resource, e.g. the number of epochs. None for anything but multi-fidelity.
trial_info__normalized_budget: The normalized budget (normalized by the maximum budget as indicated by the task).
trial_info__name: An optional name for the trial.
trial_info__checkpoint: An optional checkpoint for the trial.
# Information about the evaluated trial (tell)
## Cost related
trial_value__cost: The objective function value (lower is better).
trial_value__cost_raw: Same as `trial_value__cost`.
trial_value__cost_norm: Normalized cost, min and max are taken over all runs for one task.
## The incumbent cost
trial_value__cost_inc: The incumbent cost (best/lowest cost seen so far).
trial_value__cost_inc_norm: Incumbent cost, normalized over all runs for one task.
trial_value__cost_inc_norm_log: Logarithm of incumbent cost.
### Multi-objective
hypervolume: The hypervolume as calculated over all runs for one task.
reference_point: Reference point as determined over all runs for one task (worst seen combo).
## Time related
trial_value__time: The time the objective function took to evaluate.
trial_value__virtual_time: If the objective function is a surrogate, it can still return an evaluation time. This is marked then as virtual time.
trial_value__status: The status of the trial. Mostly hopefully `SUCCESS`.
trial_value__starttime: The start time of the objective function evaluation.
trial_value__endtime: The end time of the objective function evaluation.
# Information about the task
benchmark_id: The identifier of the benchmark collection the task belongs to.
task_type: The task type, either blackbox, multi-fidelity, multi-objective, or multi-fidelity-objective / momf.
subset_id: The subset id, mostly `None`, `dev` or `test`.
set: Another name for `subset_id`.
task.optimization_resources.n_trials: The optimization resources for the tasks in terms of number of trials.
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