ferrazzipietro/LS_Llama-2-7b-hf_adapters_en.layer1_NoQuant_16_64_0.05_2_0.0002_5EpochsBestF1Train
收藏Hugging Face2024-05-16 更新2024-06-12 收录
下载链接:
https://hf-mirror.com/datasets/ferrazzipietro/LS_Llama-2-7b-hf_adapters_en.layer1_NoQuant_16_64_0.05_2_0.0002_5EpochsBestF1Train
下载链接
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资源简介:
---
dataset_info:
features:
- name: sentence
dtype: string
- name: entities
list:
- name: id
dtype: string
- name: offsets
sequence: int64
- name: role
dtype: string
- name: semantic_type_id
dtype: string
- name: text
dtype: string
- name: type
dtype: string
- name: original_text
dtype: string
- name: original_id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence: int64
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
- name: predictions
sequence: string
- name: ground_truth_labels
sequence: string
splits:
- name: test
num_bytes: 2785371
num_examples: 681
download_size: 319580
dataset_size: 2785371
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
This dataset is primarily used for natural language processing tasks, specifically named entity recognition (NER) and related predictions. It includes features such as sentences, entity information, original text, tokens, NER tags, etc., suitable for model training and evaluation.
提供机构:
ferrazzipietro
原始信息汇总
数据集概述
数据集特征
- sentence
- 数据类型: string
- entities
- id
- 数据类型: string
- offsets
- 数据类型: sequence of int64
- role
- 数据类型: string
- semantic_type_id
- 数据类型: string
- text
- 数据类型: string
- type
- 数据类型: string
- id
- original_text
- 数据类型: string
- original_id
- 数据类型: string
- tokens
- 数据类型: sequence of string
- ner_tags
- 数据类型: sequence of int64
- input_ids
- 数据类型: sequence of int32
- attention_mask
- 数据类型: sequence of int8
- labels
- 数据类型: sequence of int64
- predictions
- 数据类型: sequence of string
- ground_truth_labels
- 数据类型: sequence of string
数据集分割
- test
- 数据大小: 2785371 bytes
- 示例数量: 681
数据集大小
- 下载大小: 319580 bytes
- 数据集总大小: 2785371 bytes
配置
- default
- 数据文件路径:
data/test-*
- 数据文件路径:



