| | --- |
| | language: |
| | - en |
| | - th |
| | - vi |
| | - zh |
| | pretty_name: HSClassify Benchmark |
| | size_categories: |
| | - n<1K |
| | task_categories: |
| | - text-classification |
| | tags: |
| | - hs-codes |
| | - trade |
| | - customs |
| | - harmonized-system |
| | - benchmark |
| | dataset_info: |
| | features: |
| | - name: text |
| | dtype: string |
| | - name: expected_hs_code |
| | dtype: string |
| | - name: category |
| | dtype: string |
| | - name: language |
| | dtype: string |
| | - name: notes |
| | dtype: string |
| | config_name: default |
| | splits: |
| | - name: test |
| | num_examples: 78 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: test |
| | path: benchmark_cases.csv |
| | --- |
| | |
| | # HSClassify Benchmark |
| |
|
| | Benchmark suite for evaluating the [HSClassify](https://github.com/JamesEBall/HSClassify_micro) HS code classifier. |
| |
|
| | ## Results (latest) |
| |
|
| | | Metric | All Cases | In-Label-Space | |
| | |--------|-----------|----------------| |
| | | Top-1 Accuracy | 79.5% | 88.6% | |
| | | Top-3 Accuracy | 82.0% | 91.4% | |
| | | Top-5 Accuracy | 83.3% | 92.9% | |
| | | Chapter Accuracy | 89.7% | 95.7% | |
| |
|
| | ### By Category |
| |
|
| | | Category | N | Top-1 | Top-3 | Top-5 | |
| | |----------|---|-------|-------|-------| |
| | | easy | 27 | 96.3% | 100% | 100% | |
| | | edge_case | 21 | 71.4% | 76.2% | 81.0% | |
| | | multilingual | 20 | 100% | 100% | 100% | |
| | | known_failure | 10 | 10.0% | 10.0% | 10.0% | |
| |
|
| | ## Test Cases |
| |
|
| | 78 hand-crafted cases in `benchmark_cases.csv` across four categories: |
| |
|
| | - **easy** (27): Common goods the model should classify correctly |
| | - **edge_case** (21): Ambiguous queries, short text, brand names |
| | - **multilingual** (20): Thai, Vietnamese, and Chinese queries |
| | - **known_failure** (10): Documents current blind spots and label-space gaps |
| |
|
| | ## Usage |
| |
|
| | Requires a trained [HSClassify_micro](https://github.com/JamesEBall/HSClassify_micro) model directory as a sibling folder (or pass `--model-dir`). |
| |
|
| | ```bash |
| | # Basic benchmark (~10s) |
| | python benchmark.py |
| | |
| | # Custom output path |
| | python benchmark.py --output results/out.json |
| | |
| | # With per-class split analysis |
| | python benchmark.py --split-analysis |
| | |
| | # Point to model directory explicitly |
| | python benchmark.py --model-dir /path/to/HSClassify_micro |
| | ``` |
| |
|
| | ## Split Analysis (training data) |
| |
|
| | Replicates the 80/20 stratified split from model training to report: |
| | - Worst 15 HS codes by F1 score |
| | - Top 20 cross-chapter confusions |
| | - Overall accuracy: **77.2%** (matches training baseline) |
| |
|
