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dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: float32
splits:
- name: train
num_examples: 6948
- name: validation
num_examples: 1985
- name: test
num_examples: 994
task_categories:
- text-regression
task_ids:
- semantic-textual-similarity
---
# Samsoup/sickr-sts
This dataset is derived from **`mteb/sickr-sts`** (SICK-R style semantic textual similarity),
which in MTEB is provided as a single split. This script shuffles that split deterministically
and produces **train / validation / test = 70% / 20% / 10%**.
**Fields**
- `sentence1` — first sentence
- `sentence2` — second sentence
- `score` — similarity / relatedness score (float32)
**Processing**
- Input: single split from `mteb/sickr-sts`
- Shuffle with a fixed seed
- 70/20/10 partition
- Keep only (`sentence1`, `sentence2`, `score`)
**Notes**
- This is meant for *regression* STS training (like STS-B style models) but on the SICK-R data.
- Reproducible: split is deterministic.
_Last updated: 2025-10-31_
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