albertvillanova HF staff commited on
Commit
d1184bd
1 Parent(s): 6429127

Add determiner_noun_agreement_with_adj_irregular_2 data files

Browse files
README.md CHANGED
@@ -464,10 +464,10 @@ dataset_info:
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  dtype: int32
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  splits:
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  - name: train
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- num_bytes: 185791
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  num_examples: 1000
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- download_size: 528528
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- dataset_size: 185791
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  - config_name: determiner_noun_agreement_with_adjective_1
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  features:
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  - name: sentence_good
@@ -1957,6 +1957,10 @@ configs:
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  data_files:
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  - split: train
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  path: determiner_noun_agreement_with_adj_irregular_1/train-*
 
 
 
 
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  ---
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  # Dataset Card for "blimp"
 
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  dtype: int32
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  splits:
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  - name: train
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+ num_bytes: 184396
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  num_examples: 1000
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+ download_size: 54064
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+ dataset_size: 184396
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  - config_name: determiner_noun_agreement_with_adjective_1
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  features:
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  - name: sentence_good
 
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  data_files:
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  - split: train
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  path: determiner_noun_agreement_with_adj_irregular_1/train-*
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+ - config_name: determiner_noun_agreement_with_adj_irregular_2
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+ data_files:
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+ - split: train
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+ path: determiner_noun_agreement_with_adj_irregular_2/train-*
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  ---
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  # Dataset Card for "blimp"
dataset_infos.json CHANGED
@@ -1027,62 +1027,50 @@
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  "features": {
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  "sentence_good": {
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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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  "sentence_bad": {
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  "_type": "Value"
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  "field": {
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  "_type": "Value"
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  "linguistics_term": {
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  "dtype": "string",
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  "_type": "Value"
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  "UID": {
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  "dtype": "string",
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  "_type": "Value"
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  "simple_LM_method": {
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- "id": null,
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  "_type": "Value"
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  "one_prefix_method": {
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  "dtype": "bool",
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- "id": null,
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  "two_prefix_method": {
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  "dtype": "bool",
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  "lexically_identical": {
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  "dtype": "bool",
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  "pair_id": {
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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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  },
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- "supervised_keys": null,
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  "builder_name": "blimp",
 
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  "config_name": "determiner_noun_agreement_with_adj_irregular_2",
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  "version": {
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  "version_str": "0.1.0",
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- "description": null,
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- "datasets_version_to_prepare": null,
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  "major": 0,
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  "minor": 1,
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  "patch": 0
@@ -1090,20 +1078,14 @@
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  "splits": {
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  "train": {
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  "name": "train",
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- "num_bytes": 185791,
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  "num_examples": 1000,
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- "dataset_name": "blimp"
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- }
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- },
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- "download_checksums": {
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- "https://raw.githubusercontent.com/alexwarstadt/blimp/master/data/determiner_noun_agreement_with_adj_irregular_2.jsonl": {
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- "num_bytes": 528528,
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- "checksum": "aa3f297a7ce0c03b5fc00458834f89e54eb855973be098497f766a390b4bc669"
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  }
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- "download_size": 528528,
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- "dataset_size": 185791,
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- "size_in_bytes": 714319
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  },
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  "determiner_noun_agreement_with_adjective_1": {
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  "description": "\nBLiMP is a challenge set for evaluating what language models (LMs) know about\nmajor grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each\ncontaining 1000 minimal pairs isolating specific contrasts in syntax,\nmorphology, or semantics. The data is automatically generated according to\nexpert-crafted grammars.\n",
 
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  "features": {
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  "sentence_good": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "sentence_bad": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "field": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "linguistics_term": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "UID": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "simple_LM_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "one_prefix_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  "two_prefix_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  "lexically_identical": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "pair_id": {
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  "dtype": "int32",
 
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  "_type": "Value"
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  }
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  },
 
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  "builder_name": "blimp",
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+ "dataset_name": "blimp",
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  "config_name": "determiner_noun_agreement_with_adj_irregular_2",
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  "version": {
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  "version_str": "0.1.0",
 
 
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  "major": 0,
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  "minor": 1,
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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": 184396,
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  "num_examples": 1000,
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+ "dataset_name": null
 
 
 
 
 
 
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  }
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  },
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+ "download_size": 54064,
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+ "dataset_size": 184396,
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+ "size_in_bytes": 238460
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  },
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  "determiner_noun_agreement_with_adjective_1": {
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  "description": "\nBLiMP is a challenge set for evaluating what language models (LMs) know about\nmajor grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each\ncontaining 1000 minimal pairs isolating specific contrasts in syntax,\nmorphology, or semantics. The data is automatically generated according to\nexpert-crafted grammars.\n",
determiner_noun_agreement_with_adj_irregular_2/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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