Referências:
emoticons
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/emoji')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 50.000 |
'train' | 45.000 |
'validation' | 5.000 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 20,
"names": [
"\u2764",
"\ud83d\ude0d",
"\ud83d\ude02",
"\ud83d\udc95",
"\ud83d\udd25",
"\ud83d\ude0a",
"\ud83d\ude0e",
"\u2728",
"\ud83d\udc99",
"\ud83d\ude18",
"\ud83d\udcf7",
"\ud83c\uddfa\ud83c\uddf8",
"\u2600",
"\ud83d\udc9c",
"\ud83d\ude09",
"\ud83d\udcaf",
"\ud83d\ude01",
"\ud83c\udf84",
"\ud83d\udcf8",
"\ud83d\ude1c"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
emoção
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/emotion')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 1421 |
'train' | 3257 |
'validation' | 374 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 4,
"names": [
"anger",
"joy",
"optimism",
"sadness"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
odiar
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/hate')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 2970 |
'train' | 9.000 |
'validation' | 1000 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"non-hate",
"hate"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
ironia
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/irony')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 784 |
'train' | 2862 |
'validation' | 955 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"non_irony",
"irony"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
ofensiva
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/offensive')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 860 |
'train' | 11916 |
'validation' | 1324 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"non-offensive",
"offensive"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
sentimento
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/sentiment')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 12284 |
'train' | 45615 |
'validation' | 2000 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"negative",
"neutral",
"positive"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
postura_aborto
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/stance_abortion')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 280 |
'train' | 587 |
'validation' | 66 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"none",
"against",
"favor"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
postura_ateísmo
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/stance_atheism')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 220 |
'train' | 461 |
'validation' | 52 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"none",
"against",
"favor"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
postura_clima
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/stance_climate')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 169 |
'train' | 355 |
'validation' | 40 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"none",
"against",
"favor"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
postura_feminista
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/stance_feminist')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 285 |
'train' | 597 |
'validation' | 67 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"none",
"against",
"favor"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
postura_hillary
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:tweet_eval/stance_hillary')
- Descrição :
TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.
- Licença : Nenhuma licença conhecida
- Versão : 1.1.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 295 |
'train' | 620 |
'validation' | 69 |
- Características :
{
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 3,
"names": [
"none",
"against",
"favor"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}