growth-cadet/Newmod_signals-deparment_split-newv1v2v3-2keval

---
dataset_info:
features:
- name: ats
dtype: string
- name: context
dtype: string
- name: sys5_obj
struct:
- name: focus_areas
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: industries
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: products_and_technologies
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: eval_crit
struct:
- name: focus_areas
dtype: float64
- name: industries
dtype: float64
- name: products_and_technologies
dtype: float64
- name: eval_values
struct:
- name: focus_areas
sequence: int64
- name: industries
sequence: int64
- name: products_and_technologies
sequence: int64
- name: uuid
dtype: string
- name: mod_sys5_obj
dtype: string
- name: gpt-3.5-turbo_cost
dtype: float64
- name: prompt
dtype: string
- name: raw_output
dtype: string
- name: deparment_obj
dtype: string
- name: gpt-4-turbo_cost
dtype: float64
- name: sysdep_obj
struct:
- name: deparment
struct:
- name: inferred
dtype: bool
- name: jobrole_deparment
dtype: string
- name: focus_areas
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: industries
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: products_and_technologies
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: prompt_dep
dtype: string
- name: raw_output_inf_dep
dtype: string
- name: mod_sysdep_obj
struct:
- name: department
struct:
- name: inferred
dtype: bool
- name: team
dtype: string
- name: toplevel_department
dtype: string
- name: focus_areas
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: industries
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: products_and_technologies
list:
- name: description
dtype: string
- name: subject
dtype: string
- name: mod_mod_sysdep_obj_raw
dtype: string
- name: department
dtype: string
- name: mod_dep_raw
dtype: string
- name: mod_answer
dtype: string
- name: mod_p&t_mod_answer_raw
dtype: string
- name: mod_p&t_mod_answer_full
dtype: string
- name: pass_pydantic
dtype: int64
- name: pass_eval_embedd
dtype: int64
splits:
- name: train
num_bytes: 71543345
num_examples: 2228
download_size: 30363232
dataset_size: 71543345
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---

原始信息汇总

数据集概述

数据集信息

特征

• ats: 类型为 string
• context: 类型为 string
• sys5_obj: 结构化数据
  • focus_areas: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • industries: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • products_and_technologies: 列表
    • description: 类型为 string
    • subject: 类型为 string
• eval_crit: 结构化数据
  • focus_areas: 类型为 float64
  • industries: 类型为 float64
  • products_and_technologies: 类型为 float64
• eval_values: 结构化数据
  • focus_areas: 序列类型为 int64
  • industries: 序列类型为 int64
  • products_and_technologies: 序列类型为 int64
• uuid: 类型为 string
• mod_sys5_obj: 类型为 string
• gpt-3.5-turbo_cost: 类型为 float64
• prompt: 类型为 string
• raw_output: 类型为 string
• deparment_obj: 类型为 string
• gpt-4-turbo_cost: 类型为 float64
• sysdep_obj: 结构化数据
  • deparment: 结构化数据
    • inferred: 类型为 bool
    • jobrole_deparment: 类型为 string
  • focus_areas: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • industries: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • products_and_technologies: 列表
    • description: 类型为 string
    • subject: 类型为 string
• prompt_dep: 类型为 string
• raw_output_inf_dep: 类型为 string
• mod_sysdep_obj: 结构化数据
  • department: 结构化数据
    • inferred: 类型为 bool
    • team: 类型为 string
    • toplevel_department: 类型为 string
  • focus_areas: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • industries: 列表
    • description: 类型为 string
    • subject: 类型为 string
  • products_and_technologies: 列表
    • description: 类型为 string
    • subject: 类型为 string
• mod_mod_sysdep_obj_raw: 类型为 string
• department: 类型为 string
• mod_dep_raw: 类型为 string
• mod_answer: 类型为 string
• mod_p&t_mod_answer_raw: 类型为 string
• mod_p&t_mod_answer_full: 类型为 string
• pass_pydantic: 类型为 int64
• pass_eval_embedd: 类型为 int64

数据分割

• train: 包含 2228 个样本，占用 71543345 字节

数据集大小

• 下载大小: 30363232 字节
• 数据集大小: 71543345 字节

配置

• config_name: default
  • data_files:
    • split: train
    • path: data/train-*