Commit
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507a95b
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Parent(s):
6b7a3b0
Convert dataset to Parquet
Browse filesConvert dataset to Parquet.
- README.md +53 -48
- adv_mnli/validation-00000-of-00001.parquet +3 -0
- dataset_infos.json +356 -1
README.md
CHANGED
@@ -19,48 +19,17 @@ task_ids:
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- natural-language-inference
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- sentiment-classification
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pretty_name: Adversarial GLUE
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tags:
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- paraphrase-identification
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- qa-nli
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dataset_info:
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- config_name: adv_sst2
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-
features:
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-
- name: sentence
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dtype: string
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-
- name: label
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-
dtype:
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class_label:
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names:
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-
'0': negative
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-
'1': positive
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- name: idx
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-
dtype: int32
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-
splits:
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-
- name: validation
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-
num_bytes: 16595
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-
num_examples: 148
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-
download_size: 40662
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-
dataset_size: 16595
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-
- config_name: adv_qqp
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features:
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-
- name: question1
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dtype: string
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-
- name: question2
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dtype: string
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-
- name: label
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dtype:
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class_label:
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names:
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-
'0': not_duplicate
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-
'1': duplicate
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-
- name: idx
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-
dtype: int32
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splits:
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-
- name: validation
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-
num_bytes: 9926
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-
num_examples: 78
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-
download_size: 40662
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-
dataset_size: 9926
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- config_name: adv_mnli
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features:
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- name: premise
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@@ -78,10 +47,10 @@ dataset_info:
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dtype: int32
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splits:
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- name: validation
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-
num_bytes:
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num_examples: 121
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-
download_size:
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-
dataset_size:
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- config_name: adv_mnli_mismatched
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features:
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- name: premise
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@@ -123,6 +92,26 @@ dataset_info:
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num_examples: 148
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download_size: 40662
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dataset_size: 34877
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- config_name: adv_rte
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features:
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- name: sentence1
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@@ -143,13 +132,29 @@ dataset_info:
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num_examples: 81
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download_size: 40662
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dataset_size: 25998
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---
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# Dataset Card for Adversarial GLUE
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- natural-language-inference
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- sentiment-classification
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pretty_name: Adversarial GLUE
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config_names:
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- adv_mnli
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- adv_mnli_mismatched
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- adv_qnli
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- adv_qqp
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- adv_rte
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- adv_sst2
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tags:
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- paraphrase-identification
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- qa-nli
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dataset_info:
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- config_name: adv_mnli
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features:
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- name: premise
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dtype: int32
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splits:
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- name: validation
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+
num_bytes: 23712
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num_examples: 121
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download_size: 13485
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dataset_size: 23712
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- config_name: adv_mnli_mismatched
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features:
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- name: premise
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num_examples: 148
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download_size: 40662
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dataset_size: 34877
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+
- config_name: adv_qqp
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features:
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- name: question1
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dtype: string
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- name: question2
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dtype: string
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- name: label
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dtype:
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class_label:
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names:
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'0': not_duplicate
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'1': duplicate
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- name: idx
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108 |
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dtype: int32
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splits:
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- name: validation
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num_bytes: 9926
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num_examples: 78
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+
download_size: 40662
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dataset_size: 9926
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- config_name: adv_rte
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features:
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- name: sentence1
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num_examples: 81
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download_size: 40662
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dataset_size: 25998
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- config_name: adv_sst2
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features:
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- name: sentence
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dtype: string
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- name: label
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dtype:
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class_label:
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names:
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'0': negative
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'1': positive
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- name: idx
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146 |
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dtype: int32
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splits:
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148 |
+
- name: validation
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149 |
+
num_bytes: 16595
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+
num_examples: 148
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+
download_size: 40662
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dataset_size: 16595
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configs:
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- config_name: adv_mnli
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data_files:
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- split: validation
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path: adv_mnli/validation-*
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---
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# Dataset Card for Adversarial GLUE
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adv_mnli/validation-00000-of-00001.parquet
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:60d669bb175d2309ace88c1b4408b203109128a021f8ae282949411a5d968d00
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size 13485
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dataset_infos.json
CHANGED
@@ -1 +1,356 @@
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-
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{
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"adv_sst2": {
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"description": "Adversarial GLUE Benchmark (AdvGLUE) is a comprehensive robustness evaluation benchmark\nthat focuses on the adversarial robustness evaluation of language models. It covers five\nnatural language understanding tasks from the famous GLUE tasks and is an adversarial\nversion of GLUE benchmark.\n",
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"citation": "@article{Wang2021AdversarialGA,\n title={Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models},\n author={Boxin Wang and Chejian Xu and Shuohang Wang and Zhe Gan and Yu Cheng and Jianfeng Gao and Ahmed Hassan Awadallah and B. Li},\n journal={ArXiv},\n year={2021},\n volume={abs/2111.02840}\n}\n",
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"homepage": "https://adversarialglue.github.io/",
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"adv_qqp": {
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"description": "Adversarial GLUE Benchmark (AdvGLUE) is a comprehensive robustness evaluation benchmark\nthat focuses on the adversarial robustness evaluation of language models. It covers five\nnatural language understanding tasks from the famous GLUE tasks and is an adversarial\nversion of GLUE benchmark.\n",
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},
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"adv_mnli": {
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"description": "Adversarial GLUE Benchmark (AdvGLUE) is a comprehensive robustness evaluation benchmark\nthat focuses on the adversarial robustness evaluation of language models. It covers five\nnatural language understanding tasks from the famous GLUE tasks and is an adversarial\nversion of GLUE benchmark.\n",
|
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