ML Emotion
ML emotion is a multilabel model that returns the emotions expressed in a sentence or subsentence. The model is composed by multiple adapters trained on diverses datasets, then fine-tuned on original goemotion dataset and its french translation. "value"'s value is always 1, since it's float value is not relevant on this task.
Emotion | Description |
---|---|
neutral | No particular emotion in this sentence. |
admiration | Finding something impressive or worthy of respect. |
amusement | Finding something funny or being entertained. |
anger | A strong feeling of displeasure or antagonism. |
annoyance | Mild anger irritation. |
approval | Having or expressing a favorable opinion. |
caring | Displaying kindness and concern for others. |
confusion | Lack of understanding uncertainty. |
curiosity | A strong desire to know or learn something. |
desire | A strong feeling of wanting something or wishing for something to happen. |
disappointment | Sadness or displeasure caused by the nonfulfillment of one’s hopes or expectations. |
disapproval | Having or expressing an unfavorable opinion. |
disgust | Revulsion or strong disapproval aroused by something unpleasant or offensive. |
embarrassment | Self-consciousness shame or awkwardness. |
excitement | Feeling of great enthusiasm and eagerness. |
fear | Being afraid or worried. |
gratitude | A feeling of thankfulness and appreciation. |
grief | Intense sorrow especially caused by someone’s death. |
joy | A feeling of pleasure and happiness. |
love | A strong positive emotion of regard and affection. |
nervousness | Apprehension worry anxiety. |
optimism | Hopefulness and confidence about the future or the success of something. |
pride | Pleasure or satisfaction due to ones own achievements or the achievements of those with whom one is closely associated. |
realization | Becoming aware of something. |
relief | Reassurance and relaxation following release from anxiety or distress. |
remorse | Regret or guilty feeling. |
sadness | Emotional pain sorrow. |
surprise | Feeling astonished startled by something unexpected. |
Main data source : @misc{demszky2020goemotions, title={GoEmotions: A Dataset of Fine-Grained Emotions}, author={Dorottya Demszky and Dana Movshovitz-Attias and Jeongwoo Ko and Alan Cowen and Gaurav Nemade and Sujith Ravi}, year={2020}, eprint={2005.00547}, archivePrefix={arXiv}, primaryClass={cs.CL} } Adapters models: @inproceedings{pfeiffer2020AdapterHub, title={AdapterHub: A Framework for Adapting Transformers}, author={Jonas Pfeiffer and Andreas R\"uckl\'{e} and Clifton Poth and Aishwarya Kamath and Ivan Vuli\'{c} and Sebastian Ruder and Kyunghyun Cho and Iryna Gurevych}, booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020): Systems Demonstrations}, year={2020}, address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.emnlp-demos.7", pages = "46--54", }
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';
<Tabs> <TabItem value="py" label="Python">
{ 'ml_emotion': { 'sentence': [ { 'type': 'admiration', 'value': 1 }, { 'type': 'realization', 'value': 1 } ], 'subsentence': [ [ { 'type': 'admiration', 'value': 1 }, { 'type': 'realization', 'value': 1 } ], [ { 'type': 'embarrassment', 'value': 1 }, { 'type': 'sadness', 'value': 1 } ] ] } }
</TabItem> <TabItem value="json" label="JSON">
{ 'ml_emotion': { 'sentence': [ { 'type': 'admiration', 'value': 1 }, { 'type': 'realization', 'value': 1 } ], 'subsentence': [ [ { 'type': 'admiration', 'value': 1 }, { 'type': 'realization', 'value': 1 } ], [ { 'type': 'embarrassment', 'value': 1 }, { 'type': 'sadness', 'value': 1 } ] ] } }
</TabItem> </Tabs>
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---
sidebar_position: 17
---
# ML Emotion
ML emotion is a multilabel model that returns the emotions expressed in a sentence or subsentence.
The model is composed by multiple adapters trained on diverses datasets, then fine-tuned on original goemotion dataset and its french translation.
"value"'s value is always 1, since it's float value is not relevant on this task.
| Emotion | Description |
|---------------- |------------------------------------------------------------------------------------------------------------------------- |
| neutral | No particular emotion in this sentence. |
| admiration | Finding something impressive or worthy of respect. |
| amusement | Finding something funny or being entertained. |
| anger | A strong feeling of displeasure or antagonism. |
| annoyance | Mild anger irritation. |
| approval | Having or expressing a favorable opinion. |
| caring | Displaying kindness and concern for others. |
| confusion | Lack of understanding uncertainty. |
| curiosity | A strong desire to know or learn something. |
| desire | A strong feeling of wanting something or wishing for something to happen. |
| disappointment | Sadness or displeasure caused by the nonfulfillment of one’s hopes or expectations. |
| disapproval | Having or expressing an unfavorable opinion. |
| disgust | Revulsion or strong disapproval aroused by something unpleasant or offensive. |
| embarrassment | Self-consciousness shame or awkwardness. |
| excitement | Feeling of great enthusiasm and eagerness. |
| fear | Being afraid or worried. |
| gratitude | A feeling of thankfulness and appreciation. |
| grief | Intense sorrow especially caused by someone’s death. |
| joy | A feeling of pleasure and happiness. |
| love | A strong positive emotion of regard and affection. |
| nervousness | Apprehension worry anxiety. |
| optimism | Hopefulness and confidence about the future or the success of something. |
| pride | Pleasure or satisfaction due to ones own achievements or the achievements of those with whom one is closely associated. |
| realization | Becoming aware of something. |
| relief | Reassurance and relaxation following release from anxiety or distress. |
| remorse | Regret or guilty feeling. |
| sadness | Emotional pain sorrow. |
| surprise | Feeling astonished startled by something unexpected. |
Main data source : ```
@misc{demszky2020goemotions, title={GoEmotions: A Dataset of Fine-Grained Emotions}, author={Dorottya Demszky and Dana Movshovitz-Attias and Jeongwoo Ko and Alan Cowen and Gaurav Nemade and Sujith Ravi}, year={2020}, eprint={2005.00547}, archivePrefix={arXiv}, primaryClass={cs.CL} } Adapters models: @inproceedings{pfeiffer2020AdapterHub, title={AdapterHub: A Framework for Adapting Transformers}, author={Jonas Pfeiffer and Andreas R\"uckl\'{e} and Clifton Poth and Aishwarya Kamath and Ivan Vuli\'{c} and Sebastian Ruder and Kyunghyun Cho and Iryna Gurevych}, booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020): Systems Demonstrations}, year={2020}, address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.emnlp-demos.7", pages = "46--54", }```
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
<Tabs>
<TabItem value="py" label="Python">
```py
{
'ml_emotion': {
'sentence': [
{
'type': 'admiration', 'value': 1
},
{
'type': 'realization', 'value': 1
}
],
'subsentence': [
[
{
'type': 'admiration', 'value': 1
},
{
'type': 'realization', 'value': 1
}
],
[
{
'type': 'embarrassment', 'value': 1
},
{
'type': 'sadness', 'value': 1
}
]
]
}
}
```
</TabItem>
<TabItem value="json" label="JSON">
```json
{
'ml_emotion': {
'sentence': [
{
'type': 'admiration', 'value': 1
},
{
'type': 'realization', 'value': 1
}
],
'subsentence': [
[
{
'type': 'admiration', 'value': 1
},
{
'type': 'realization', 'value': 1
}
],
[
{
'type': 'embarrassment', 'value': 1
},
{
'type': 'sadness', 'value': 1
}
]
]
}
}
```
</TabItem>
</Tabs>
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