Maloba

Document reading (OCR)

Qwen2-VL 2B + QLoRA

Read a photographed Lingala document, printed or handwritten, and extract its text.

Result

88,7 % de caractères justes (CER 11,3 %) on 50 test examples. Source : E01. Voir la page Résultats.

Mesures automatiques (E01)
MesureValeur
Caractères justes88,7 %
CER (caractères erronés)11,30 %
Exactitude stricte28,0 %

Jugement humain (trois validateurs) : 32 % de sorties correctes à la majorité, 92 % correctes ou récupérables ; accord α 0,665 : exploitable.

The measurements, as charts

Document reading: three ways of countingCharacter accuracy says how many letters are right; strict accuracy counts only lines that are perfect end to end; human validation judges the meaning.
0255075100Correct characters88,7 %Recoverable outputs (human)92,0 %Strict accuracy28,0 %

Source : E01, E07

Show the chart data
MeasureValue %
Correct characters88,7
Recoverable outputs (human)92,0
Strict accuracy28,0

What it does well, what it does badly

What it does well

  • 88.7 % correct characters; 92 % of outputs judged recoverable by the human validators.
  • The only human result with sufficient agreement between validators (α 0.665): usable.
  • Apache 2.0 licence: usable commercially.

What it does badly

  • Strict accuracy of 28 %: only one line in four is perfect end to end.
  • Small test set (50 examples) and images of uneven quality.
  • Handwriting is harder than print.

How it was built

Socle Qwen/Qwen2-VL-2B-Instruct, adapté par qLoRA, LoRA rang 32, jetons ɔ ɛ Ɔ Ɛ ajoutés. Données : 417 exemples image–texte. Détail dans le rapport F03.

Licence

Apache-2.0 : usable commercially. Un modèle garde la licence de son modèle de base, quelle que soit celle des données d'entraînement. Gouvernance des données.