hgissbkh/AskUbuntu-reranking

---
dataset_info:
- config_name: GIST-large-Embedding-v0
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 65114748
num_examples: 375
download_size: 50418728
dataset_size: 65114748
- config_name: ember-v1
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 65114748
num_examples: 375
download_size: 50399760
dataset_size: 65114748
- config_name: multilingual-e5-base
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 48986748
num_examples: 375
download_size: 37952498
dataset_size: 48986748
- config_name: multilingual-e5-large
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 65114748
num_examples: 375
download_size: 50190084
dataset_size: 65114748
- config_name: multilingual-e5-small
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 24794748
num_examples: 375
download_size: 19275206
dataset_size: 24794748
- config_name: mxbai-embed-large-v1
features:
- name: query
dtype: string
- name: docs
sequence: string
- name: query_enc
sequence: float64
- name: docs_enc
sequence:
sequence: float64
- name: cos_scores
sequence: float64
- name: target
sequence: int64
splits:
- name: train
num_bytes: 65114748
num_examples: 375
download_size: 50406818
dataset_size: 65114748
configs:
- config_name: GIST-large-Embedding-v0
data_files:
- split: train
path: GIST-large-Embedding-v0/train-*
- config_name: ember-v1
data_files:
- split: train
path: ember-v1/train-*
- config_name: multilingual-e5-base
data_files:
- split: train
path: multilingual-e5-base/train-*
- config_name: multilingual-e5-large
data_files:
- split: train
path: multilingual-e5-large/train-*
- config_name: multilingual-e5-small
data_files:
- split: train
path: multilingual-e5-small/train-*
- config_name: mxbai-embed-large-v1
data_files:
- split: train
path: mxbai-embed-large-v1/train-*
---

原始信息汇总

数据集概述

1. GIST-large-Embedding-v0

• 配置名称: GIST-large-Embedding-v0
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，65114748字节
• 下载大小: 50418728字节
• 数据集大小: 65114748字节

2. ember-v1

• 配置名称: ember-v1
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，65114748字节
• 下载大小: 50399760字节
• 数据集大小: 65114748字节

3. multilingual-e5-base

• 配置名称: multilingual-e5-base
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，48986748字节
• 下载大小: 37952498字节
• 数据集大小: 48986748字节

4. multilingual-e5-large

• 配置名称: multilingual-e5-large
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，65114748字节
• 下载大小: 50190084字节
• 数据集大小: 65114748字节

5. multilingual-e5-small

• 配置名称: multilingual-e5-small
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，24794748字节
• 下载大小: 19275206字节
• 数据集大小: 24794748字节

6. mxbai-embed-large-v1

• 配置名称: mxbai-embed-large-v1
• 特征:
  • query: 字符串类型
  • docs: 字符串序列类型
  • query_enc: 浮点序列类型
  • docs_enc: 浮点序列类型
  • cos_scores: 浮点序列类型
  • target: 整数序列类型
• 分割:
  • train: 375个样本，65114748字节
• 下载大小: 50406818字节
• 数据集大小: 65114748字节