Delete legacy dataset_infos.json

dataset_infos.json

@@ -1,65 +0,0 @@
-{
-    "amttl": {
-        "description": "Chinese word segmentation (CWS) trained from open source corpus faces dramatic performance drop\nwhen dealing with domain text, especially for a domain with lots of special terms and diverse\nwriting styles, such as the biomedical domain. However, building domain-specific CWS requires\nextremely high annotation cost. In this paper, we propose an approach by exploiting domain-invariant\nknowledge from high resource to low resource domains. Extensive experiments show that our mode\nachieves consistently higher accuracy than the single-task CWS and other transfer learning\nbaselines, especially when there is a large disparity between source and target domains.\n\nThis dataset is the accompanied medical Chinese word segmentation (CWS) dataset.\nThe tags are in BIES scheme.\n\nFor more details see https://www.aclweb.org/anthology/C18-1307/\n",
-        "citation": "@inproceedings{xing2018adaptive,\n  title={Adaptive multi-task transfer learning for Chinese word segmentation in medical text},\n  author={Xing, Junjie and Zhu, Kenny and Zhang, Shaodian},\n  booktitle={Proceedings of the 27th International Conference on Computational Linguistics},\n  pages={3619--3630},\n  year={2018}\n}\n",
-        "homepage": "https://www.aclweb.org/anthology/C18-1307/",
-        "license": "",
-        "features": {
-            "id": {
-                "dtype": "string",
-                "_type": "Value"
-            },
-            "tokens": {
-                "feature": {
-                    "dtype": "string",
-                    "_type": "Value"
-                },
-                "_type": "Sequence"
-            },
-            "tags": {
-                "feature": {
-                    "names": [
-                        "B",
-                        "I",
-                        "E",
-                        "S"
-                    ],
-                    "_type": "ClassLabel"
-                },
-                "_type": "Sequence"
-            }
-        },
-        "builder_name": "parquet",
-        "dataset_name": "amttl",
-        "config_name": "amttl",
-        "version": {
-            "version_str": "1.0.0",
-            "major": 1,
-            "minor": 0,
-            "patch": 0
-        },
-        "splits": {
-            "train": {
-                "name": "train",
-                "num_bytes": 1132196,
-                "num_examples": 3063,
-                "dataset_name": null
-            },
-            "validation": {
-                "name": "validation",
-                "num_bytes": 324358,
-                "num_examples": 822,
-                "dataset_name": null
-            },
-            "test": {
-                "name": "test",
-                "num_bytes": 328509,
-                "num_examples": 908,
-                "dataset_name": null
-            }
-        },
-        "download_size": 274351,
-        "dataset_size": 1785063,
-        "size_in_bytes": 2059414
-    }
-}