lhoestq HF staff commited on
Commit
59f3661
1 Parent(s): 4ae5a32

Add 'en-ext' config data files

Browse files
README.md CHANGED
@@ -44,6 +44,26 @@ dataset_info:
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  num_examples: 670
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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:
@@ -62,6 +82,14 @@ configs:
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  - split: test
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  path: en/test-*
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  default: true
 
 
 
 
 
 
 
 
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  ---
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  # Amazon Multilingual Counterfactual Dataset
 
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  num_examples: 670
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  download_size: 382768
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  dataset_size: 685860
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+ - config_name: en-ext
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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: 1053699
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+ num_examples: 8000
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+ - name: validation
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+ num_bytes: 87748
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+ num_examples: 666
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+ - name: test
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+ num_bytes: 174870
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+ num_examples: 1334
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+ download_size: 731478
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+ dataset_size: 1316317
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  configs:
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  - config_name: de
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  data_files:
 
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  - split: test
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  path: en/test-*
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  default: true
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+ - config_name: en-ext
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+ data_files:
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+ - split: train
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+ path: en-ext/train-*
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+ - split: validation
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+ path: en-ext/validation-*
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+ - split: test
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+ path: en-ext/test-*
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  ---
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  # Amazon Multilingual Counterfactual Dataset
dataset_infos.json CHANGED
@@ -293,28 +293,22 @@
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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": "en-ext",
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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
@@ -322,41 +316,26 @@
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  "splits": {
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  "train": {
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  "name": "train",
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- "num_bytes": 1054707,
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  "num_examples": 8000,
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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": 87840,
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  "num_examples": 666,
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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": 175045,
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  "num_examples": 1334,
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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/EN-ext_train.tsv": {
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- "num_bytes": 857747,
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- "checksum": "eb741daf73fec09af23cb194b6424f533c96280770c7c8a60d87b211a0ae6f72"
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- },
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- "data/EN-ext_valid.tsv": {
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- "num_bytes": 71464,
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- "checksum": "3e054c3c83e893cbec0640aeb2d79bf8fabe1040951d127da3f2fa9a69c05002"
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- },
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- "data/EN-ext_test.tsv": {
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- "num_bytes": 142278,
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- "checksum": "7891a0dc26417905718389402f6ea57f1a714f81bd258dbd134d5689e2fb7fd6"
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  }
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  },
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- "download_size": 1071489,
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- "post_processing_size": null,
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- "dataset_size": 1317592,
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- "size_in_bytes": 2389081
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  },
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  "ja": {
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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": "en-ext",
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  "version": {
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  "version_str": "1.0.0",
 
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  "major": 1,
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  "minor": 0,
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  "patch": 0
 
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  "splits": {
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  "train": {
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  "name": "train",
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+ "num_bytes": 1053699,
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  "num_examples": 8000,
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+ "dataset_name": null
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  },
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  "validation": {
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  "name": "validation",
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+ "num_bytes": 87748,
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  "num_examples": 666,
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+ "dataset_name": null
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  },
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  "test": {
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  "name": "test",
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+ "num_bytes": 174870,
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  "num_examples": 1334,
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+ "dataset_name": null
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  },
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+ "download_size": 731478,
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+ "dataset_size": 1316317,
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+ "size_in_bytes": 2047795
 
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  },
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  "ja": {
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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",
en-ext/test-00000-of-00001.parquet ADDED
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en-ext/train-00000-of-00001.parquet ADDED
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en-ext/validation-00000-of-00001.parquet ADDED
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