Model card
Oracle-BERT (HowSumm-Method).
Unknownextractive1 current SOTA
Oracle upper bound using BERT similarity for HowSumm-Method. Not a trainable model — represents an upper bound on extractive performance.
§ 02 · Benchmarks
Every benchmark Oracle-BERT (HowSumm-Method) has a recorded score for.
| # | Benchmark | Area · Task | Metric | Value | Rank | Date | Source |
|---|---|---|---|---|---|---|---|
| 01 | howsumm-method | Computer Vision · Optical Character Recognition | rouge-1 | 63.2% | #1 | — | source ↗ |
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area
Where Oracle-BERT (HowSumm-Method) actually performs.
§ 05 · Related models
Other Unknown models scored on Codesota.
CRAFT
Unknown params · 21 results
GPT-2-Large (fine-tuning)
Unknown params · 20 results
HTLM (fine-tuning)
Unknown params · 20 results
TextFuseNet (ResNeXt-101)
Unknown params · 16 results
MixNet
Unknown params · 13 results
PAN
Unknown params · 12 results
SPCNET
Unknown params · 12 results
TESTR
Unknown params · 12 results
§ 06 · Sources & freshness
Where these numbers come from.
paper
1
result
1 of 1 rows marked verified.