llamaindex-vdr-en-train-preprocessed

This dataset is a preprocessed English subset of llamaindex/vdr-multilingual-train, prepared for training multimodal Sentence Transformer embedding models on document screenshot retrieval.

Changes from the original dataset

The original llamaindex/vdr-multilingual-train dataset stores hard negatives as a list of ID strings that reference other rows. This dataset makes two key changes:

1. English only: Only the English subset (53,512 samples) is included.
2. Resolved negatives as images: 4 out of the 16 hard negatives are resolved from IDs into the actual document screenshot images, stored as negative_0 through negative_3. This makes the dataset directly usable for training with Sentence Transformers without any additional preprocessing.

Dataset Structure

Each sample contains:

Column	Type	Description
query	string	A synthetic text query associated with the document screenshot
image	image	The positive document screenshot (PDF page rendered as an image)
negative_0	image	Hard negative document screenshot (closest)
negative_1	image	Hard negative document screenshot
negative_2	image	Hard negative document screenshot
negative_3	image	Hard negative document screenshot (furthest)

Configs

Config	Samples	Description
full	53,512	All English samples
train	10,000	The first 10,000 samples (0–9,999) from the full dataset
eval	300	The next 300 samples (10,000–10,299) from the full dataset

You can certainly train on the full dataset, and then you're recommended to make your own eval/test splits. Do not combine full and eval, as you'll train and evaluate on the same data.

Usage

from datasets import load_dataset

# Load the training split
train_dataset = load_dataset("tomaarsen/llamaindex-vdr-en-train-preprocessed", "train", split="train")

# Load the evaluation split
eval_dataset = load_dataset("tomaarsen/llamaindex-vdr-en-train-preprocessed", "eval", split="train")

# Load all English samples
full_dataset = load_dataset("tomaarsen/llamaindex-vdr-en-train-preprocessed", "full", split="train")

Training

This dataset can be used to finetune a multimodal Sentence Transformer model for document screenshot embedding. See the training example for a full training script.

Source

This dataset is derived from llamaindex/vdr-multilingual-train, which consists of 500k multilingual query-image samples collected and generated from public internet PDFs. Queries were synthetically generated using VLMs (gemini-1.5-pro and Qwen2-VL-72B). See the original dataset card for full details on the data collection and curation process.