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pandas
lhoestq HF staff commited on
Commit
4ae5a32
1 Parent(s): 237a372

Add 'de' config data files

Browse files
README.md CHANGED
@@ -4,7 +4,27 @@ language:
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  - en
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  - ja
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  dataset_info:
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- config_name: en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  features:
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  - name: text
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  dtype: string
@@ -25,6 +45,14 @@ dataset_info:
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  download_size: 382768
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  dataset_size: 685860
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  configs:
 
 
 
 
 
 
 
 
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  - config_name: en
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  data_files:
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  - split: train
 
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  - en
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  - ja
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  dataset_info:
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+ - config_name: de
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+ features:
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+ - name: text
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+ dtype: string
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+ - name: label
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+ dtype: int32
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+ - name: label_text
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_bytes: 839355
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+ num_examples: 5600
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+ - name: validation
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+ num_bytes: 72051
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+ num_examples: 466
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+ - name: test
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+ num_bytes: 142977
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+ num_examples: 934
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+ download_size: 610356
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+ dataset_size: 1054383
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+ - config_name: en
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  features:
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  - name: text
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  dtype: string
 
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  download_size: 382768
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  dataset_size: 685860
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  configs:
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+ - config_name: de
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+ data_files:
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+ - split: train
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+ path: de/train-*
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+ - split: validation
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+ path: de/validation-*
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+ - split: test
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+ path: de/test-*
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  - config_name: en
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  data_files:
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  - split: train
dataset_infos.json CHANGED
@@ -116,28 +116,22 @@
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  "features": {
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  "text": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  },
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  "label": {
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  "dtype": "int32",
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- "id": null,
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  "_type": "Value"
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  },
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  "label_text": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  }
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  },
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- "post_processed": null,
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- "supervised_keys": null,
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- "task_templates": null,
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- "builder_name": "amazon_counterfactual",
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  "config_name": "de",
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  "version": {
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  "version_str": "1.0.0",
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- "description": "",
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  "major": 1,
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  "minor": 0,
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  "patch": 0
@@ -145,41 +139,26 @@
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  "splits": {
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  "train": {
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  "name": "train",
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- "num_bytes": 840063,
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  "num_examples": 5600,
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- "dataset_name": "amazon_counterfactual"
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  },
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  "validation": {
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  "name": "validation",
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- "num_bytes": 72118,
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  "num_examples": 466,
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- "dataset_name": "amazon_counterfactual"
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  },
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  "test": {
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  "name": "test",
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- "num_bytes": 143102,
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  "num_examples": 934,
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- "dataset_name": "amazon_counterfactual"
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- }
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- },
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- "download_checksums": {
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- "data/DE_train.tsv": {
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- "num_bytes": 705786,
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- "checksum": "52710850d8bef30422421f4ca238a4d3e76d44e1e01e2458320b949cd66fbcd1"
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- },
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- "data/DE_valid.tsv": {
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- "num_bytes": 60990,
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- "checksum": "677831289a71ebba856dfaecec92dfc9dfade9a954f8e50c923407a1fcda981a"
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- },
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- "data/DE_test.tsv": {
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- "num_bytes": 120712,
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- "checksum": "ccfb853849a85ea747fbb435bad7c50336bd2c28c523be4479535a8872870476"
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  }
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  },
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- "download_size": 887488,
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- "post_processing_size": null,
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- "dataset_size": 1055283,
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- "size_in_bytes": 1942771
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  },
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  "en": {
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  "description": "The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form \u2013 If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false).\n",
 
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  "features": {
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  "text": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "label": {
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  "dtype": "int32",
 
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  "_type": "Value"
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  },
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  "label_text": {
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  "dtype": "string",
 
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  "_type": "Value"
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  }
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  },
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+ "builder_name": "parquet",
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+ "dataset_name": "amazon_counterfactual",
 
 
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  "config_name": "de",
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  "version": {
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  "version_str": "1.0.0",
 
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  "major": 1,
136
  "minor": 0,
137
  "patch": 0
 
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  "splits": {
140
  "train": {
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  "name": "train",
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+ "num_bytes": 839355,
143
  "num_examples": 5600,
144
+ "dataset_name": null
145
  },
146
  "validation": {
147
  "name": "validation",
148
+ "num_bytes": 72051,
149
  "num_examples": 466,
150
+ "dataset_name": null
151
  },
152
  "test": {
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  "name": "test",
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+ "num_bytes": 142977,
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  "num_examples": 934,
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+ "dataset_name": null
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  },
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+ "download_size": 610356,
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+ "dataset_size": 1054383,
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+ "size_in_bytes": 1664739
 
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  },
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  "en": {
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  "description": "The dataset contains sentences from Amazon customer reviews (sampled from Amazon product review dataset) annotated for counterfactual detection (CFD) binary classification. Counterfactual statements describe events that did not or cannot take place. Counterfactual statements may be identified as statements of the form \u2013 If p was true, then q would be true (i.e. assertions whose antecedent (p) and consequent (q) are known or assumed to be false).\n",
de/test-00000-of-00001.parquet ADDED
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de/train-00000-of-00001.parquet ADDED
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de/validation-00000-of-00001.parquet ADDED
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