## Model description
This model was trained on the XED dataset and achieved  
validation loss: 0.5995  
validation acc: 84.28% (ROC-AUC)  

Labels are based on Plutchik's model of emotions and may be combined:
![image](https://user-images.githubusercontent.com/12978899/122398897-f60d2500-cf97-11eb-8991-61e68f4ea1fc.png)

### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.8.0
- Tokenizers 0.10.3

{}
transformers pytorch distilbert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

## Model description
This model was trained on the XED dataset and achieved  
validation loss: 0.5995  
validation acc: 84.28% (ROC-AUC)  

Labels are based on Plutchik's model of emotions and may be combined:
!image

### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.8.0
- Tokenizers 0.10.3

## Model description
This model was trained on the XED dataset and achieved  
validation loss: 0.5995  
validation acc: 84.28% (ROC-AUC)  

Labels are based on Plutchik's model of emotions and may be combined:
!image ### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.8.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
 ## Model description
This model was trained on the XED dataset and achieved  
validation loss: 0.5995  
validation acc: 84.28% (ROC-AUC)  

Labels are based on Plutchik's model of emotions and may be combined:
!image ### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.8.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #distilbert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
## Model description
This model was trained on the XED dataset and achieved  
validation loss: 0.5995  
validation acc: 84.28% (ROC-AUC)  

Labels are based on Plutchik's model of emotions and may be combined:
!image### Framework versions
- Transformers 4.6.1
- Pytorch 1.8.1+cu101
- Datasets 1.8.0
- Tokenizers 0.10.3