Fix the byte-identity claim, the placeholder dataset id and the extras description
Browse files
README.md
CHANGED
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@@ -53,7 +53,7 @@ dataset exists for, and it is asserted at build time.
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```
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data/<config>/test-*.parquet the evaluation set, one row per case
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extras/<config>/ the same arrays
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case_index.parquet case id, edge id, label, typology, HT weight
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ml_baselines/weights/ all three ensemble members, 5 seeds each
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ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble members
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@@ -73,13 +73,13 @@ ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble
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| `ht_weight` | float64 | Horvitz-Thompson importance weight. Apply when aggregating P, R and F1. |
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| `n_transactions` | int32 | Transactions in the two-hop subgraph. |
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| `n_tokens_approx` | int32 | Approximate prompt length. |
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| `typed_graph_text` | string | The typed-graph prompt,
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("
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print(ds[0]["case_id"], ds[0]["label"], ds[0]["typology"])
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print(ds[0]["typed_graph_text"][:200])
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```
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@@ -146,8 +146,8 @@ genuinely null. Rows are in `case_id` order, which is the join key against the r
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predictions and the rubric annotations, so the file is deliberately not sorted to put labelled
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rows first.
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To browse labels and weights without pulling the prompt column, use `extras/<config>/`
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## Case identifiers
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```
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data/<config>/test-*.parquet the evaluation set, one row per case
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extras/<config>/ the same arrays as .npy, plus the GFP tensors
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case_index.parquet case id, edge id, label, typology, HT weight
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ml_baselines/weights/ all three ensemble members, 5 seeds each
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ml_baselines/test_probs/ full-test-split probabilities for the 3 ensemble members
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| `ht_weight` | float64 | Horvitz-Thompson importance weight. Apply when aggregating P, R and F1. |
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| `n_transactions` | int32 | Transactions in the two-hop subgraph. |
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| `n_tokens_approx` | int32 | Approximate prompt length. |
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| `typed_graph_text` | string | The typed-graph prompt the evaluated models were given, identical except for the case identifier token (see Case identifiers). |
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset("natnitaract/amlcompact-eval", "HI-Small", split="test")
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print(ds[0]["case_id"], ds[0]["label"], ds[0]["typology"])
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print(ds[0]["typed_graph_text"][:200])
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```
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predictions and the rubric annotations, so the file is deliberately not sorted to put labelled
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rows first.
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To browse labels and weights without pulling the prompt column, use `extras/<config>/`: the
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same arrays as `.npy`, plus `case_index.parquet` as a join table, 1.5 MB in total.
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## Case identifiers
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