📊 VERIFIED METRICS TABLE: Rakīm AI (رَقِيم)
Below is the verified dataset of digital metrics compiled from the project's verification sample reports, test logs, presentation JSON configurations, and service scripts.
1. Character Error Rate (CER) and Model Metrics
| Metric | Value | Dataset / Sample | Source File | Confidence | Notes |
|---|---|---|---|---|---|
| Trained Sample CER | 3.29% (96.71% Acc) | 3 training pages (Maghrebi) | عينات_التحقق/النتائج.md |
High | Measures how well the model memorizes its training subset. |
| Unseen Test CER | 7.50% (92.50% Acc) | 51 frozen test pages (Maghrebi) | عينات_التحقق/النتائج.md |
High | Primary metric for general readability and model performance. |
| Baseline exp6 (No LM) CER | 7.48% | RASAM Maghrebi dataset | presentation_dashboard/data/metrics.json |
High | Verified in direct comparison logs. |
| LM exp6 (With LM) CER | 6.79% | RASAM Maghrebi dataset | presentation_dashboard/data/metrics.json |
High | Shows a 0.69% absolute error reduction using local LM. |
| Baseline TariMa (No LM) CER | 10.27% | TariMa manuscript dataset | presentation_dashboard/data/metrics.json |
High | Generalization baseline for TariMa hands. |
| LM TariMa (With LM) CER | 8.81% | TariMa manuscript dataset | presentation_dashboard/data/metrics.json |
High | Shows a 1.46% absolute error reduction using local LM. |
| Legacy Model CER | Unusable (Garbage Text) | Maghrebi scripts | المقارنة_الموحدة.md |
High | Model reg(96.5) fails completely on historical Maghrebi hands. |
2. Segmentation and Page Layout Metrics
| Page/Sample | Ground Truth (GT) Lines | Produced Lines (seg_best) |
Source File | Status / Analysis |
|---|---|---|---|---|
| Page 1926 (Simple Layout) | 9 lines | 11 lines | عينات_التحقق/النتائج.md |
Close to perfect segment alignment. |
| Page 417 (Margins/Hawahin) | 13 lines | 43 lines | عينات_التحقق/النتائج.md |
Severe over-segmentation due to marginalia. |
| Page 1982 (Dense + Margins) | 37 lines | 53 lines | عينات_التحقق/النتائج.md |
Over-segmentation of page borders/marginal notes. |
| Page 1960 (Layout Split) | 26 lines (Main) | 30 lines (26 Main / 4 Margins) | demo_package/المقارنات_الرقمية.md |
Layout split correctly separates margins from text body. |
3. Database Catalog Statistics
| Metric | Value | Source File | Status |
|---|---|---|---|
| Total Cataloged Works | 35,632 | catalog_stats.json |
Compiled from OpenITI (13,364) & FIHRIST (15,543). |
| Total Manuscript Copies | 49,980 | catalog_stats.json |
Total registered manuscript copies. |
| Works with Multiple Copies | 6,003 (16.85%) | catalog_stats.json |
Works residing in more than one library collection. |
| Average Copies per Work | 1.4 | catalog_stats.json |
Global duplication factor. |
4. Execution Latency Metrics (CPU vs. GPU)
| Task | Device | Time (Seconds) | Source File / Logs | Notes |
|---|---|---|---|---|
| Neural Segmentation (BLLA) | CPU (Docker) | ~11.0s | demo_package/README_DEMO.md |
BLLA is structurally heavy. |
| Text Recognition | CPU (Docker) | ~4.0s | demo_package/README_DEMO.md |
Direct Kraken PyTorch execution. |
| Total Inference Page Latency | CPU (Docker) | ~14.0–16.0s | demo_package/README_DEMO.md |
Time required to process a single raw page. |
| Fast Segmentation | CPU (Direct) | 1.0–3.0s | config.py |
Settings flag FAST_SEGMENTATION=true. |
| Total Inference Page Latency | GPU (RTX 4050) | ~4.0s | demo_package/README_DEMO.md |
Substantial acceleration (almost 4x speedup). |
| Inference Page Latency | Cache Hit | 0.0s | ocr.py |
Immediate response if image hash matches cache database. |