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---
language:
- en
license: apache-2.0
tags:
- text
pretty_name: MS MARCO hard negatives
size_categories:
- "100K<n<1M"
source_datasets:
- "BeIR/msmarco"
- "sentence-transformers/msmarco-hard-negatives"
task_categories:
- sentence-similarity
dataset_info:
config_name: default
features:
- name: query
dtype: string
- name: positive
sequence: string
- name: negative
sequence: string
splits:
- name: train
num_bytes: 89609915
num_examples: 502939
train-eval-index:
- config: default
task: sentence-similarity
splits:
train_split: train
eval_split: test
configs:
- config_name: default
data_files:
- split: train
path: "data/train/*"
---
# MS MARCO hard negatives dataset
A dataset in a [nixietune](https://github.com/nixiesearch/nixietune) compatible format:
```json
{
"query": ")what was the immediate impact of the success of the manhattan project?",
"pos": [
"The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
],
"neg": [
"Abstract. The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs.",
"The pivotal engineering and scientific success of the Twentieth century was the Manhattan Project. The Manhattan Project assimilated concepts and leaders from all scientific fields and engineering disciplines to construct the first two atomic bombs."
]
}
```
This is the original [BeIR-msmarco](https://huggingface.co/datasets/BeIR/msmarco) joined with the [msmarco-hard-negatives](https://huggingface.co/datasets/sentence-transformers/msmarco-hard-negatives) dataset with the following splits:
* train: 502939 queries, only positives.
## Usage
```python
from datasets import load_dataset
data = load_dataset('nixiesearch/ms-marco-hard-negatives')
print(data["train"].features)
```
## License
Apache 2.0 |