---
dataset_info:
  features:
  - name: article
    dtype: string
  - name: embedding
    sequence: float32
  splits:
  - name: train
    num_bytes: 6526015558
    num_examples: 614664
  download_size: 4974256567
  dataset_size: 6526015558
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: other
task_categories:
  - sentence-similarity
language:
  - en
pretty_name: CCNEWS with Embeddings (dim=1024)
tags:
  - embeddings
  - sentence-transformers
  - similarity-search
  - parquet
  - ccnews
---



# Dataset Card for `ccnews_all-roberta-large-v1_dim1024`

This dataset contains English news articles from the [CCNEWS dataset](https://huggingface.co/datasets/sentence-transformers/ccnews) along with their corresponding 1024-dimensional embeddings, precomputed using the `sentence-transformers/all-roberta-large-v1` model.

Note: If you are only interested in the raw embeddings (without the associated text), a compact version is available in the related repository: [ScarlettMagdaleno/ccnews-embeddings-dim1024](https://huggingface.co/datasets/ScarlettMagdaleno/ccnews-embeddings-dim1024).

## Dataset Details

### Dataset Description

Each entry in this dataset is stored in Apache Parquet format, split into multiple files for scalability. Each record contains two fields:

- `'article'`: The original news article text.
- `'embedding'`: A 1024-dimensional list representing the output of the `sentence-transformers/all-roberta-large-v1` encoder.

- **Curated by:** Scarlett Magdaleno
- **Language(s) (NLP):** English
- **License:** Other (the dataset is a derivative of the CCNEWS dataset, which may carry its own license)

### Dataset Sources

- **Base Text Dataset:** [sentence-transformers/ccnews](https://huggingface.co/datasets/sentence-transformers/ccnews)
- **Embedding Model:** [sentence-transformers/all-roberta-large-v1](https://huggingface.co/sentence-transformers/all-roberta-large-v1)

## Dataset Creation

### Curation Rationale

The dataset was created to enable fast and reproducible similarity search experiments, as well as to provide a resource where the relationship between the raw text and its embedding is explicitly retained.

### Source Data

#### Data Collection and Processing

- Texts were taken from the CCNEWS dataset available on Hugging Face.
- Each article was passed through the encoder `all-roberta-large-v1` from the `sentence-transformers` library.
- The resulting embeddings were stored along with the article in Parquet format for efficient disk usage and interoperability.

#### Who are the source data producers?

- The original texts come from English-language news websites.
- The embeddings were generated and curated by Scarlett Magdaleno.

- **Repository:** https://huggingface.co/datasets/ScarlettMagdaleno/ccnews_all-roberta-large-v1_dim1024

## Uses

### Direct Use

This dataset is suitable for:

- Training and evaluating similarity search models.
- Experiments involving semantic representation of news content.
- Weakly supervised learning using embeddings as targets or features.
- Benchmarks for contrastive or clustering approaches.

### Out-of-Scope Use

- Not suitable for generative modeling tasks (no labels, no dialogues, no instructions).
- Does not include metadata such as timestamps, URLs, or categories.

## Dataset Structure

Each Parquet file contains a table with two columns:

- `article` (string): The raw article text.
- `embedding` (list[float]): A list of 1024 float values representing the semantic embedding.

### Format

- Storage format: Apache Parquet.
- Total records: same as CCNEWS — approximately 614,664 articles.
- Split: the dataset is divided into multiple parquet files for better loading performance.

### Example Record

```json
{
  "article": "U.S. President signs new environmental policy...",
  "embedding": [0.023, -0.117, ..., 0.098]  # 1024 values
}