| # Splits |
|
|
| > **Training split only.** This repository publishes the `dev_task_names` half |
| > of each pinned split. The held-out/test tasks are not included, and neither |
| > are the published splits that are not the pin. Every split file here is |
| > reproduced byte-for-byte from the source repository, so `assignment_sha256` |
| > still verifies and `heldout_task_names` still names the absent test tasks. |
| |
| One folder per dataset. The file inside is the pinned resolved train/test |
| assignment over the tasks of that dataset, published without its private random |
| seed. |
| |
| The tasks themselves stay in the dataset folder at the top level of this |
| repository, so the `dev_task_names` listed in |
| `splits/tau3-bench/tau3-banking-70-s001.json` are directories under |
| `tau3-bench/tasks/`. The `heldout_task_names` are not. |
| |
| ``` |
| splits/ |
| QuantitativeFinance-Bench/ |
| healthbench/ |
| hle/ |
| tau3-bench/ |
| ``` |
| |
| ## Which split we use |
| |
| Several datasets carry more than one published split. Exactly one of them is |
| the pin: the split that the skilltrainbench launch skills hardcode and that the |
| reported results were produced on. Only the pin is published here; the others |
| stay in the source repository, for replication and for pipeline tests, and a |
| number produced on them is not comparable to a number produced on the pin. |
| |
| | Dataset | Pinned split | Task set | Dev / train | Held-out / test | Learner pool | Claude Code `max_turns` | OpenHands `max_iterations` | |
| |---|---|---|---:|---:|---:|---:|---:| |
| | QuantitativeFinance-Bench | `qf-medhard-strat-80-s005` | `medium_hard` | 54 | 14 | 160M | 41 | 45 | |
| | healthbench | `hb-hardbeh-s002` | `hard_behavioural` | 200 | 160 | 80M | 11 | 12 | |
| | hle | `hle-stem517-s001` | `stem517` | 412 | 105 | 400M | 36 | 40 | |
| | tau3-bench | `tau3-banking-70-s001` | `banking_knowledge` | 67 | 30 | 360M | 51 | 60 | |
|
|
| **The four benchmark pools sum to 1,000M and that total is a hard limit.** Each |
| pool is `dev x 4 x` the mean weighted tokens (input + 5 x output) of a |
| within-cutoff GLM 5.3 Flash attempt, the four scaled together to sum to 1B, |
| which is what a two-person hackathon team's $200 of GLM buys. The mean counts an |
| over-cutoff attempt with the tokens it had reached at the cut rather than |
| dropping it. |
|
|
| The learner pool is the `--budget-tokens` pool for skill formation. It caps the |
| learner only. Curator spend, judge spend and simulator spend are metered in |
| their own pools and are never charged against it. |
|
|
| The tool-call cutoff is one number per benchmark, applied identically to every |
| learner. Claude Code `max_turns` counts model responses and OpenHands |
| `max_iterations` counts loop steps, so neither is an exact tool-call ceiling; |
| the numbers above are the serial-call allowance, with OpenHands given about 20% |
| more. **A cutoff hit is a failed attempt**, and its rate is reported per arm |
| next to the lift. |
|
|
| The published results predate this table. They were measured at 100M |
| (QuantitativeFinance-Bench), 100M (healthbench), 300M (tau3-bench) and 500M |
| (hle), with healthbench at 4 turns and the others effectively uncapped. Those |
| runs stay valid as published, but a new run and an old run are not on the same |
| budget. Rescoring an old run under the new cutoffs is not valid either: the |
| probe signal, and so the skill, would have differed. |
|
|
| Each pinned split verifies against these digests: |
|
|
| | Dataset | `assignment_sha256` | |
| |---|---| |
| | QuantitativeFinance-Bench | `f256dfa217a335f88a925c088b78289553de0a9cadaec96153d682cabf60ec0f` | |
| | healthbench | `32b8ab7615506a55e9fa3ca89ee1d6e68f66a771f62636f2876d2ec99ca68cfb` | |
| | tau3-bench | `90d6bcc7f58b181725dc4c0f21960b1459c6b9bacdb6ef09f2fb7eda30fb27b6` | |
| | hle | `3b1755f035bf7135bfdd4b40bf376cb157cc7f7a49739e48da92e35be06d5aeb` | |
|
|
| ## Pins that are not splits |
|
|
| A run is only reproducible if the environment is pinned too. These values live |
| in `src/skilltrainbench/harbor_policy.py` in the skilltrainbench repository and |
| are applied when a task tree is staged, so a task Dockerfile in this repository |
| may name an unpinned tag while the run that used it did not. |
|
|
| | Dataset | Base image | Upstream code pinned at build time | |
| |---|---|---| |
| | QuantitativeFinance-Bench | `doenermannti/finance-bench-sandbox@sha256:a6766c8b32cae3425feaddb8d9bac185de866323307290b7c74aed30f9c928ef` | none | |
| | healthbench | `python:3.12-slim@sha256:2fe5997d249a808b8eeea52c58a1dbffbba28754dc11699ef5c029f2d818ce79` | `openai/simple-evals@496e4570446e9f0499a00557a231a440c446df76` | |
| | tau3-bench | `python:3.12-slim@sha256:2fe5997d249a808b8eeea52c58a1dbffbba28754dc11699ef5c029f2d818ce79` | `sierra-research/tau2-bench@672227c6b6` | |
| | hle | `python:3.11-slim@sha256:9534e5a8e315485d4061ed659af0fd78a284c015f9b73661b41d6bab25604534` | `harbor-framework/harbor-datasets@37db108843a49bb31a592e37a75e2c40dc3f9749` | |
|
|
| The tau3-bench images clone `tau2-bench` while they build, so that clone has to |
| be pinned or the image silently tracks upstream. Override it with |
| `STBENCH_TAU3BENCH_TAU2_COMMIT` only when you mean to. |
|
|
| ### Grader and simulator models |
|
|
| These are configuration, not dataset content, and a run records what it used. |
|
|
| - healthbench. The grader is the pinned `simple-evals` HealthBench grader, |
| vendored as `healthbench_eval.py` with SHA-256 |
| `b763d8c1f53ecd165f0d170a32bc948216b3dfeadafe238b2083328e1af4b2df`. The |
| official judge configuration for the benchmark is `gpt-4.1-2025-04-14` at |
| temperature `0.5`. The reported `hb-hardbeh-s002` run deliberately deviates |
| and used `claude-haiku-4-5-20251001` at temperature `0`, with its own 40M |
| judge pool. Say which one you used. |
| - tau3-bench. The simulated user and the natural-language assertion judge run |
| through `TAU2_USER_MODEL` and `TAU2_NL_ASSERTIONS_MODEL`, both |
| `openai/claude-sonnet-4-6` with `TAU2_USER_REASONING_EFFORT=low` in the |
| reported run. They are metered in a separate simulator pool. |
|
|
| ## Selecting a split |
|
|
| ```bash |
| --benchmark tau3bench --task-set banking_knowledge --split-id tau3-banking-70-s001 |
| ``` |
|
|
| `dev_task_names` is the training set and `heldout_task_names` is the test set. |
| Split identifiers are immutable. If a task set definition or the task bytes |
| change, create a new identifier rather than reusing one; the loader fails |
| closed when `task_set_definition_sha256` or `selected_source_snapshot_sha256` |
| no longer matches. |
|
|
| ## Fields |
|
|
| - `schema_version`: split artifact schema. |
| - `split_id`: immutable identifier for this assignment. |
| - `benchmark`: skilltrainbench benchmark adapter. |
| - `task_set`: selected task-set identifier. |
| - `train_ratio_in_split`: requested train proportion. |
| - `stratified`: whether the assignment was stratified. |
| - `dev_task_names`: development names; treat these as train tasks. |
| - `heldout_task_names`: held-out names; treat these as test tasks. |
| - `counts`: resolved development and held-out counts. |
| - `strata`: counts per stratum, where the assignment was stratified. |
| - `task_set_definition_sha256`: digest of the task-set definition. |
| - `selected_source_snapshot_sha256`: digest of the selected task bytes used to |
| resolve this assignment. |
| - `assignment_sha256`: digest of the public, seed-stripped assignment. |
|
|
| The private random seed is removed from every file published here. It stays in |
| the skilltrainbench repository under the ignored `private/splits/` directory. |
|
|
| ## Download |
|
|
| ```bash |
| hf download armin-aptura/skilltrainbench-public --repo-type dataset \ |
| --include "splits/**" --local-dir . |
| ``` |
|
|
| For one dataset and its split together: |
|
|
| ```bash |
| hf download armin-aptura/skilltrainbench-public --repo-type dataset \ |
| --include "tau3-bench/**" --include "splits/tau3-bench/**" --local-dir . |
| ``` |
|
|
