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README.md

@@ -1,28 +1,93 @@
----
-dataset_info:
-  features:
-  - name: instruction
-    dtype: string
-  - name: input
-    dtype: string
-  - name: output
-    dtype: string
-  - name: task
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3805942
-    num_examples: 10000
-  - name: validation
-    num_bytes: 766914
-    num_examples: 2000
-  download_size: 1005699
-  dataset_size: 4572856
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
----
+# Orbura AutoScientist Data Visualization Dataset
+
+## Dataset Description
+
+A synthetic instruction-tuning corpus for data visualization tasks, built for
+the [AutoScientist Challenge](https://adaptionlabs.ai/blog/autoscientist-challenge)
+Part 2 (Data Visualization). Every example is deterministically generated —
+no human annotation, no LLM-generated labels — so the ground truth is exact
+and reproducible.
+
+### Task types
+
+| Task | Weight | Description |
+|---|---|---|
+| `chart_qa` | 45% | Arithmetic, comparison, and trend questions about chart data (max, min, sum, avg, median, range, pct_total, ratio, rank, above_avg, trend, difference, counterfactual, percentage_change) |
+| `chart_to_code` | 15% | Generate matplotlib code from a chart type + data table |
+| `fix_code` | 10% | Repair common matplotlib bugs (typos, missing imports, mismatched lengths, invalid kwargs, string values, swapped axes) |
+| `code_to_desc` | 10% | Describe what a matplotlib code block produces, including key statistics |
+| `style_transfer` | 10% | Modify an existing plot (change chart type, add grid, rotate labels, change color) |
+| `chart_choice` | 5% | Select the most appropriate chart type for given data |
+| `data_to_code` | 5% | Convert CSV data into a matplotlib chart |
+
+### Chart types covered
+
+- **line** — trend visualization
+- **bar** — category comparison
+- **scatter** — correlation
+- **pie** — proportion of a whole
+
+### Multimodal extension
+
+A 100-row multimodal pilot (`generate_multimodal_pilot.py`) generates rendered
+chart images (PNG) with chart-QA pairs. This extends the text-only dataset with
+visual reasoning: the model sees a rendered chart and answers questions about
+it. The pilot covers bar, grouped bar, stacked bar, line, multi-line, scatter,
+pie, donut, area, and mixed (bar + line overlay) chart types.
+
+## Files
+
+| File | Rows | Description |
+|---|---|---|
+| `adaption_train_10k.jsonl` | 10,000 | Training set (column-mapped for Adaption) |
+| `adaption_val_2k.jsonl` | 2,000 | Validation set (held-out) |
+| `adaption_pilot_500.jsonl` | 500 | Small pilot for quick iteration |
+| `train_10k.jsonl` | 10,000 | Training set (raw, pre-Adaption-mapping) |
+| `val_2k.jsonl` | 2,000 | Validation set (raw, pre-Adaption-mapping) |
+| `multimodal_pilot/` | 100 | Rendered chart images + metadata |
+
+## Schema
+
+| Field | Description |
+|---|---|
+| `instruction` | Task prompt |
+| `input` | Context (data table, CSV, code, or chart metadata) |
+| `output` | Ground-truth completion (deterministic) |
+| `task` | Sub-task name |
+| `category` | Always `data_visualization` |
+| `messages` | Chat-formatted version for SFT |
+
+## Generation
+
+Generated deterministically by `generate_full.py` with seed 42 (train) and
+seed 2024 (val). The Adaption column mapping is applied by
+`prepare_adaption.py`.
+
+```bash
+python3 generate_full.py        # → train_10k.jsonl + val_2k.jsonl
+python3 prepare_adaption.py     # → adaption_train_10k.jsonl + adaption_val_2k.jsonl
+python3 generate_multimodal_pilot.py  # → multimodal_pilot/
+```
+
+## Augmentation
+
+The dataset is designed to be augmented via Adaption Adaptive Data with:
+- `reasoning_traces`: enabled
+- `prompt_rephrase`: **disabled** (rewrites system prompts, causing
+  train/inference mismatch — learned from Part 1 post-mortem)
+- `deduplication`: enabled
+
+## Usage
+
+```python
+import json
+
+with open("adaption_train_10k.jsonl") as f:
+    for line in f:
+        example = json.loads(line)
+        # example["instruction"], example["input"], example["output"], example["task"]
+```
+
+## License
+
+Apache 2.0