Datasets:
Clarify dataset and trace documentation; improve plots and add command distributions
Browse files- README.md +28 -15
- seta_v2/trace_stats/README.md +21 -1
- seta_v2/trace_stats/data/provenance.json +12 -2
- seta_v2/trace_stats/plots/all-models-trace-commands.png +3 -0
- seta_v2/trace_stats/plots/all-models-trace-distributions.png +2 -2
- seta_v2/trace_stats/plots/qwen3-30b-instruct-2507-trace-commands.png +3 -0
- seta_v2/trace_stats/plots/qwen3-30b-instruct-2507-trace-distributions.png +2 -2
- seta_v2/trace_stats/plots/qwen3-30b-thinking-trace-commands.png +3 -0
- seta_v2/trace_stats/plots/qwen3-30b-thinking-trace-distributions.png +2 -2
README.md
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Datasets repaired and filtered using the [OT-next-data validation protocol](https://github.com/MLI-lab/OT-next-data/blob/main/validation/PROTOCOL.md).
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- **V1:** environment reliability and rule-based task-quality repairs. Build/setup, no-op and reference checks where reference solutions exist.
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- **V2:**
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## Dataset sizes and composition
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**V1: 42,166 kept, patched tasks across 8 data sources.**
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**V2: 7,
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Percentages are each source's share of that version's total in the current published snapshots.
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| Dataset | V1 tasks | Share of V1 | V2 tasks | Share of V2 |
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| --- | ---: | ---: | ---: | ---: |
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| BugsInPy | [489](bugsinpy_v1) | 1.16% | [65](bugsinpy_v2) | 0.85% |
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| CrossCodeEval | [6,710](crosscodeeval_v1) | 15.91% | [863](crosscodeeval_v2) | 11.
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| TermiGen | [3,336](termigen_v1) | 7.91% | [2,277](termigen_v2) | 29.
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| SETA | [3,107](seta_v1) | 7.37% | [2,
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| CalibForge | [5,317](calibforge_v1) | 12.61% | [84](calibforge_v2) | 1.
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| ScaleSWE | [16,786](scaleswe_v1) | 39.81% | [292](scaleswe_v2) | 3.
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| SWE-Lego | [4,277](swelego_v1) | 10.14% | [575](swelego_v2) | 7.
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| EndlessTerminals | [2,144](endless_v1) | 5.08% | [1,323](endless_v2) | 17.
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| **Total** | **42,166** | **100%** | **7,
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`tasks.parquet` contains kept tasks. V1 includes `archive.parquet`; V2 exclusions can be recovered from V1 using the selection manifest. V2 reuses V1 images. ScaleSWE uses its original Docker Hub images, with optional Apptainer caches.
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## Download tasks and images
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```
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Datasets repaired and filtered using the [OT-next-data validation protocol](https://github.com/MLI-lab/OT-next-data/blob/main/validation/PROTOCOL.md).
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- **V1:** environment reliability and rule-based task-quality repairs. Build/setup, no-op and reference checks where reference solutions exist.
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- **V2:** keep tasks solved at least once by an evaluated model. Includes partial results where a success is already recorded; each README lists models, attempt counts and coverage.
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## Dataset sizes and composition
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**V1: 42,166 kept, patched tasks across 8 data sources.**
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**V2: 7,684 tasks solved at least once across the same 8 data sources.** V2 is a subset of V1, not additional tasks.
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Percentages are each source's share of that version's total in the current published snapshots.
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| Dataset | V1 tasks | Share of V1 | V2 tasks | Share of V2 |
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| --- | ---: | ---: | ---: | ---: |
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| BugsInPy | [489](bugsinpy_v1) | 1.16% | [65](bugsinpy_v2) | 0.85% |
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| CrossCodeEval | [6,710](crosscodeeval_v1) | 15.91% | [863](crosscodeeval_v2) | 11.23% |
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| TermiGen | [3,336](termigen_v1) | 7.91% | [2,277](termigen_v2) | 29.63% |
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| SETA | [3,107](seta_v1) | 7.37% | [2,205](seta_v2) | 28.70% |
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| CalibForge | [5,317](calibforge_v1) | 12.61% | [84](calibforge_v2) | 1.09% |
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| ScaleSWE | [16,786](scaleswe_v1) | 39.81% | [292](scaleswe_v2) | 3.80% |
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| SWE-Lego | [4,277](swelego_v1) | 10.14% | [575](swelego_v2) | 7.48% |
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| EndlessTerminals | [2,144](endless_v1) | 5.08% | [1,323](endless_v2) | 17.22% |
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| **Total** | **42,166** | **100%** | **7,684** | **100%** |
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`tasks.parquet` contains kept tasks. V1 includes `archive.parquet`. Tasks left out of V2 remain in V1; `metadata/selection.json` lists which tasks were kept. V2 reuses V1 images. ScaleSWE uses its original Docker Hub images, with optional Apptainer caches.
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## Download tasks and images
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)
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```
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## Trace stats
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[SETA trajectory statistics and plots](seta_v2/trace_stats/README.md) cover turns, tokens, elapsed time, commands and termination outcomes.
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Each attempt gets one termination label automatically from the harness stop reason and recorded exception type. No LLM judge assigns these labels. Termination describes why the agent stopped; the verifier reward records whether its work passed.
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| Outcome | Meaning |
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| Task complete | The agent declared and confirmed completion; verification can still fail. |
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| tmux session closed | The terminal session disappeared before normal completion confirmation. |
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| Task timeout | The agent exceeded its allowed runtime. |
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| Repeated output truncation | Three consecutive truncated responses could not be recovered into usable responses. |
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| Context recovery failure | The harness failed to recover usable context for another model request. |
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| Other limits | A recorded turn, context, output or task-memory limit stopped the agent. |
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| Error | An exception stopped the run without a more specific termination label. |
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| Not recorded | No termination reason was recorded. |
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Errors are also grouped by component: **environment/terminal** (container or tmux errors, which may be agent-caused), **verifier** (checking failed to run or finish normally, not a normal reward of 0), **model server** (model API or serving failures), and **other** (unmapped exceptions). An attempt can have multiple exceptions and appear in several error groups; this panel covers all attempts, not just the “Error” termination bar.
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seta_v2/trace_stats/README.md
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## Plots
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Termination reasons and recorded error categories:
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Model-specific plots: [Instruct measurements](plots/qwen3-30b-instruct-2507-trace-distributions.png), [Instruct outcomes](plots/qwen3-30b-instruct-2507-trace-outcomes.png), [Thinking measurements](plots/qwen3-30b-thinking-trace-distributions.png), [Thinking outcomes](plots/qwen3-30b-thinking-trace-outcomes.png).
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## Data
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- [Summary](data/summary.json): overall and per-model statistics.
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The two `context_recovery_failure` attempts hit a harness recovery bug: repeated truncated-response retries exhausted the remaining context and requested zero output tokens. They are not normal context-limit stops.
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“tmux session closed” means the agent terminal disappeared before normal completion confirmation. The raw stop reason remains `session_ended`. All 649 attempts were verified: 53 passed and 596 failed. The [closure audit](data/tmux_session_audit.json) records the command evidence and unresolved cases.
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## Plots
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Turns, token totals and elapsed time per attempt:
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Token axes use scientific notation (for example, `1e5` means 100,000). Agent elapsed time covers the whole agent phase, including model calls, terminal work and waits; verifier elapsed time covers the checking phase.
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The largest-turn panel shows the largest recorded input-plus-output token total for a turn. A turn can include several model calls during recovery. The older `peak_context_tokens` and `peak_context_fraction` fields therefore do not measure actual context occupancy: a ratio of 2 means a recorded turn totaled twice the configured context size, not that one request used twice the context window.
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For samples of at least 100 attempts, a panel zooms to the 99th percentile when the maximum is more than 1.5 times that percentile. Its title reports how many values lie beyond the displayed range; full values remain in the data. Otherwise it shows the full range.
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Termination reasons and recorded error categories:
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Model-specific plots: [Instruct measurements](plots/qwen3-30b-instruct-2507-trace-distributions.png), [Instruct outcomes](plots/qwen3-30b-instruct-2507-trace-outcomes.png), [Thinking measurements](plots/qwen3-30b-thinking-trace-distributions.png), [Thinking outcomes](plots/qwen3-30b-thinking-trace-outcomes.png).
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## Command distribution
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Frequency of recognized submitted command/tool labels across all attempts; these are not counts of successful executions. Unclassified and assignment-only labels are excluded and counted in the figure title. Complex shell syntax is not fully parsed. Each occurrence has equal weight, so longer attempts contribute more commands.
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Model-specific command plots: [Instruct](plots/qwen3-30b-instruct-2507-trace-commands.png), [Thinking](plots/qwen3-30b-thinking-trace-commands.png).
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## Data
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- [Summary](data/summary.json): overall and per-model statistics.
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The two `context_recovery_failure` attempts hit a harness recovery bug: repeated truncated-response retries exhausted the remaining context and requested zero output tokens. They are not normal context-limit stops.
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“tmux session closed” means the agent terminal disappeared before normal completion confirmation. The raw stop reason remains `session_ended`. All 649 attempts were verified: 53 passed and 596 failed. The [closure audit](data/tmux_session_audit.json) records the command evidence and unresolved cases.
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## Generation and resource accounting
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Stage 7 computes trajectory metrics, and the report exporter generates plots automatically. This dataset overview is rendered and published by a separate export script; it does not refresh itself when new jobs finish.
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Per-trajectory CPU and GPU hours were not measured. Agent elapsed time is wall time, not CPU usage or exclusive GPU time: concurrent attempts share the model server. Scheduler allocation-hours could be reported per job, but assigning them to individual trajectories would require an explicit estimation method.
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seta_v2/trace_stats/data/provenance.json
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"figures": [
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"../plots/qwen3-30b-instruct-2507-trace-distributions.png",
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"../plots/qwen3-30b-instruct-2507-trace-outcomes.png",
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"../plots/qwen3-30b-thinking-trace-distributions.png",
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"../plots/qwen3-30b-thinking-trace-outcomes.png",
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"../plots/all-models-trace-distributions.png",
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"../plots/all-models-trace-outcomes.png"
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],
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"metric_implementation_sha256": "b12538bef1f15032164d4655b65b24080cdad119ebd6df025fe172a43eb32adf",
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"termination_corrections": [
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"display_labels": {
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"session_ended": "tmux session closed"
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"session_closure_audit": "tmux_session_audit.json"
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}
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"figures": [
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"../plots/qwen3-30b-instruct-2507-trace-distributions.png",
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"../plots/qwen3-30b-instruct-2507-trace-outcomes.png",
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"../plots/qwen3-30b-instruct-2507-trace-commands.png",
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"../plots/qwen3-30b-thinking-trace-distributions.png",
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"../plots/qwen3-30b-thinking-trace-outcomes.png",
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"../plots/qwen3-30b-thinking-trace-commands.png",
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"../plots/all-models-trace-distributions.png",
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"../plots/all-models-trace-outcomes.png",
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"../plots/all-models-trace-commands.png"
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],
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"metric_implementation_sha256": "b12538bef1f15032164d4655b65b24080cdad119ebd6df025fe172a43eb32adf",
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"termination_corrections": [
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"display_labels": {
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"session_ended": "tmux session closed"
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"session_closure_audit": "tmux_session_audit.json",
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"plotting": {
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"implementation_sha256": "8c29f3b4116c34aac0adba654144f505d283fb4ee751eb1139d99575ec902ceb",
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"histogram_range": "For n >= 100 and max > 1.5*p99, display 0..p99 with an explicit omitted-tail count; otherwise 0..max.",
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"command_weights": "Raw recognized command/tool occurrence counts; unclassified/assignment labels excluded.",
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"context_note": "Legacy peak_context_* fields derive from per-turn token totals, which may aggregate multiple requests; not actual context occupancy.",
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"per_trajectory_resource_hours": "Not measured; elapsed time must not be interpreted as exclusive GPU time or CPU usage."
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}
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}
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