TEKNOFEST_train.ipynb was used for fine tuning a turkish bert model. The goal is sentiment analysis for turkish text.

https://github.com/OnurSahh/Teknofest_NLP_Acikhack2023

            OUTPUT
Label / Offensive or not / Target
          
Label_0 = OFFENSIVE and INSULT

Label_1 = OFFENSIVE and RACIST

Label_2 = OFFENSIVE and SEXIST

Label_3 = OFFENSIVE and PROFANITY

Label_4 = NOT OFFENSIVE and OTHER

Label_5 = OFFENSIVE and OTHER

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

TEKNOFEST_train.ipynb was used for fine tuning a turkish bert model. The goal is sentiment analysis for turkish text.

URL

            OUTPUT
Label / Offensive or not / Target
          
Label_0 = OFFENSIVE and INSULT

Label_1 = OFFENSIVE and RACIST

Label_2 = OFFENSIVE and SEXIST

Label_3 = OFFENSIVE and PROFANITY

Label_4 = NOT OFFENSIVE and OTHER

Label_5 = OFFENSIVE and OTHER

TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
