Datasetpublic

vkehfdl1/banana-vidorev3-fullpipe

Banana ViDoRe v3 Fullpipe Nano Banana Pro full-pipeline synthetic training data for ViDoRe v3 finance and industrial domains. This repository contains 4670 training records and 40190 unique referenced images across domain-separated ColFlor/ColQwen training splits. Images are included in the repository and paths in each JSONL are relative to that domain directory. Generated at: 2026-06-29T09:39:01.644860+00:00 Layout finance/train.jsonl finance/metadata.json… See the full description on the dataset page: https://huggingface.co/datasets/vkehfdl1/banana-vidorev3-fullpipe.

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Dataset Card

Banana ViDoRe v3 Fullpipe

Nano Banana Pro full-pipeline synthetic training data for ViDoRe v3 finance and industrial domains.

This repository contains 4670 training records and 40190 unique referenced images across domain-separated ColFlor/ColQwen training splits. Images are included in the repository and paths in each JSONL are relative to that domain directory.

Generated at: 2026-06-29T09:39:01.644860+00:00

Layout

text

finance/train.jsonl
finance/metadata.json
finance/images/...
industrial/train.jsonl
industrial/metadata.json
industrial/images/...
metadata.json

Splits

domain	records	positive pages	hard negative pages	unique images
finance	2853	12411	12409	24820
industrial	1817	7685	7685	15370

Usage

python

from banana.training.data.dataset import BananaDataset

finance = BananaDataset("finance/train.jsonl", num_hard_negatives=4)
industrial = BananaDataset("industrial/train.jsonl", num_hard_negatives=4)

When loading from the Hub with the Banana training scripts, use the domain JSONL path:

bash

python -m banana.training.scripts.train \
  --data-path hf://datasets/vkehfdl1/banana-vidorev3-fullpipe/finance/train.jsonl

Schema

Each JSONL row contains:

—query: synthetic training query
—positive_pages: relative image paths under the same domain directory
—hard_negative_pages: relative hard-negative image paths
—metadata.domain: finance or industrial
—metadata.source_dataset: source ViDoRe v3 dataset name
—metadata.negative_method: banana_fullpipe

The data was generated for training/adaptation only. Use held-out ViDoRe test splits for evaluation.