References:
in
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:polemo2/in')
- Description:
The PolEmo2.0 is a set of online reviews from medicine and hotels domains. The task is to predict the sentiment of a review. There are two separate test sets, to allow for in-domain (medicine and hotels) as well as out-of-domain (products and university) validation.
- License: CC BY-NC-SA 4.0
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
722 |
'train' |
5783 |
'validation' |
723 |
- Features:
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"num_classes": 4,
"names": [
"__label__meta_amb",
"__label__meta_minus_m",
"__label__meta_plus_m",
"__label__meta_zero"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
out
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:polemo2/out')
- Description:
The PolEmo2.0 is a set of online reviews from medicine and hotels domains. The task is to predict the sentiment of a review. There are two separate test sets, to allow for in-domain (medicine and hotels) as well as out-of-domain (products and university) validation.
- License: CC BY-NC-SA 4.0
- Version: 1.1.0
- Splits:
Split | Examples |
---|---|
'test' |
494 |
'train' |
5783 |
'validation' |
494 |
- Features:
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"num_classes": 4,
"names": [
"__label__meta_amb",
"__label__meta_minus_m",
"__label__meta_plus_m",
"__label__meta_zero"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}