Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-label-classification
Languages:
German
Size:
1K - 10K
License:
File size: 1,489 Bytes
aecc4f0 8191b2d aecc4f0 8191b2d aecc4f0 8191b2d aecc4f0 8191b2d aecc4f0 8191b2d aecc4f0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | {
"n_classes": 9,
"labels": [
{
"id": 0,
"name": "Beauty/Joy"
},
{
"id": 1,
"name": "Sadness"
},
{
"id": 2,
"name": "Uneasiness"
},
{
"id": 3,
"name": "Vitality"
},
{
"id": 4,
"name": "Awe/Sublime"
},
{
"id": 5,
"name": "Suspense"
},
{
"id": 6,
"name": "Annoyance"
},
{
"id": 7,
"name": "Humor"
},
{
"id": 8,
"name": "Nostalgia"
}
],
"train_label_rule": "dual-annotator union ≤2 + poem-level subset of XMLGold (Nostalgia coverage, source=XMLGold_to_train)",
"test_label_rule": "remaining XMLGold emo1/emo2",
"counts": {
"train": {
"Suspense": 265,
"Beauty/Joy": 1036,
"Uneasiness": 610,
"Sadness": 611,
"Awe/Sublime": 261,
"Vitality": 439,
"Humor": 184,
"Annoyance": 120,
"Nostalgia": 38
},
"test": {
"Vitality": 166,
"Sadness": 172,
"Beauty/Joy": 267,
"Suspense": 151,
"Humor": 74,
"Annoyance": 168,
"Uneasiness": 154,
"Awe/Sublime": 154,
"Nostalgia": 32
},
"all": {
"Suspense": 416,
"Beauty/Joy": 1303,
"Uneasiness": 764,
"Sadness": 783,
"Awe/Sublime": 415,
"Vitality": 605,
"Humor": 258,
"Annoyance": 288,
"Nostalgia": 70
}
}
} |