This model is mainly focussed on extracting the sentiment on tweets regarding bitcoin. The model was trained on manually on labeled data with rubrix (https://www.rubrix.ml/). The training set approximately contained 500 samples and 500 test samples. The cardiffnlp/twitter-xlm-roberta-base-sentiment (https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) was used as weak classifier and also as base-model for finetuning.


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

This model is mainly focussed on extracting the sentiment on tweets regarding bitcoin. The model was trained on manually on labeled data with rubrix (URL The training set approximately contained 500 samples and 500 test samples. The cardiffnlp/twitter-xlm-roberta-base-sentiment (URL was used as weak classifier and also as base-model for finetuning.


TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #xlm-roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 
