--- task_categories: - token-classification --- # AutoTrain Dataset for project: full-dfsep23-xlmrobbase ## Dataset Description This dataset has been automatically processed by AutoTrain for project full-dfsep23-xlmrobbase. ### Languages The BCP-47 code for the dataset's language is unk. ## Dataset Structure ### Data Instances A sample from this dataset looks as follows: ```json [ { "feat_Unnamed: 0.1": 0, "feat_Unnamed: 0": 0, "tokens": [ "terms", "fm", "door", "Quinto", "Di", "Treviso", "to", "HKG", "/", "Tablo/", "2", "Plts", "/", "348", "Kgs/", "3.84", "Cbm", "/", "Cargo", "ready:", "6", "Jun", "Ciao", "Ale", ";", "120*80*200", "-", "348", "kgs.", "Totali", ";", "pick", "up", "address:", ";", "Viale", "dell'Industria,", "26", ";", "310", "55", "QUINTO", "DI", "TREVISO", ";", "And", "kindly", "quote", "upto", "HKG", "under", "CPT", "terms", ";", "Grazie", ";", "alessio", ";", "Alessio", "Rovetta", ";", "Italy", "Seafreight", "Product", "Manager", ";", "[New", "Logo", "Mail]", ";", "S.P.", "14", "Rivoltana", "Km", "9,500", ";", "20060", "-", "Vignate", "(MI)", ";", "*si", "accede", "al", "sito", "da", "via", "Bruno", "Buozzi", "snc,", "Liscate", "(MI)", ";", "Telefono:", "+39", "236766530", ";", "Cellulare:", "+39", "3427670429", ";", "E-mail:", "a.rovetta@erixmar.com", ";", "In", "relazione", "all'entrata", "in", "vigore", "del", "cos\u00ec", "detto", "GDPR,", "General", "Data", "Protection", "Regulation,", "anche", "noi", "in", "ERIXMAR", "SRL" ], "tags": [ 0, 0, 0, 12, 12, 12, 0, 5, 0, 0, 15, 10, 21, 21, 21, 20, 20, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 19, 19, 0, 0, 0, 0, 0, 0, 12, 12, 12, 0, 11, 11, 12, 12, 12, 0, 0, 0, 0, 0, 5, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] }, { "feat_Unnamed: 0.1": 412, "feat_Unnamed: 0": 417, "tokens": [ "Buongiorno", ";", "Prego", "quotare", ";", "n.", "1", "CASSA", "160", "X", "210", "X", "150", "KG", "1.50", ";", ";", ";", "da", "10127", "Torino", ";", "CIF", "DAMMAM", "PORT", "-", "SAUDI", "ARABIA" ], "tags": [ 0, 0, 0, 0, 0, 0, 15, 10, 8, 8, 8, 8, 8, 21, 21, 0, 0, 0, 0, 11, 12, 0, 7, 5, 5, 5, 6, 6 ] } ] ``` ### Dataset Fields The dataset has the following fields (also called "features"): ```json { "feat_Unnamed: 0.1": "Value(dtype='int64', id=None)", "feat_Unnamed: 0": "Value(dtype='int64', id=None)", "tokens": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)", "tags": "Sequence(feature=ClassLabel(names=['O', 'commodity', 'company', 'delivery_cap', 'delivery_location', 'delivery_port', 'delivery_state', 'incoterms', 'measures', 'nan', 'package_type', 'pickup_cap', 'pickup_location', 'pickup_port', 'pickup_state', 'quantity', 'stackable', 'total_quantity', 'total_volume', 'total_weight', 'volume', 'weight'], id=None), length=-1, id=None)" } ``` ### Dataset Splits This dataset is split into a train and validation split. The split sizes are as follow: | Split name | Num samples | | ------------ | ------------------- | | train | 613 | | valid | 269 |