তথ্যসূত্র:
en_notated
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:xed_en_fi/en_annotated')
- বর্ণনা :
A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.
- লাইসেন্স : লাইসেন্স: ক্রিয়েটিভ কমন্স অ্যাট্রিবিউশন 4.0 আন্তর্জাতিক লাইসেন্স (CC-BY)
- সংস্করণ : 1.1.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'train' | 17528 |
- বৈশিষ্ট্য :
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 9,
"names": [
"neutral",
"anger",
"anticipation",
"disgust",
"fear",
"joy",
"sadness",
"surprise",
"trust"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
en_neutral
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:xed_en_fi/en_neutral')
- বর্ণনা :
A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.
- লাইসেন্স : লাইসেন্স: ক্রিয়েটিভ কমন্স অ্যাট্রিবিউশন 4.0 আন্তর্জাতিক লাইসেন্স (CC-BY)
- সংস্করণ : 1.1.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'train' | 9675 |
- বৈশিষ্ট্য :
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"num_classes": 9,
"names": [
"neutral",
"anger",
"anticipation",
"disgust",
"fear",
"joy",
"sadness",
"surprise",
"trust"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}
fi_ annotated
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:xed_en_fi/fi_annotated')
- বর্ণনা :
A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.
- লাইসেন্স : লাইসেন্স: ক্রিয়েটিভ কমন্স অ্যাট্রিবিউশন 4.0 আন্তর্জাতিক লাইসেন্স (CC-BY)
- সংস্করণ : 1.1.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'train' | 14449 |
- বৈশিষ্ট্য :
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 9,
"names": [
"neutral",
"anger",
"anticipation",
"disgust",
"fear",
"joy",
"sadness",
"surprise",
"trust"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
fi_neutral
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:xed_en_fi/fi_neutral')
- বর্ণনা :
A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to
show that XED performs on par with other similar datasets and is therefore a useful tool for
sentiment analysis and emotion detection.
- লাইসেন্স : লাইসেন্স: ক্রিয়েটিভ কমন্স অ্যাট্রিবিউশন 4.0 আন্তর্জাতিক লাইসেন্স (CC-BY)
- সংস্করণ : 1.1.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'train' | 10794 |
- বৈশিষ্ট্য :
{
"sentence": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"num_classes": 9,
"names": [
"neutral",
"anger",
"anticipation",
"disgust",
"fear",
"joy",
"sadness",
"surprise",
"trust"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}