task_categories:token-classification region:us
---
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<mailto: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 |
