# Model Description

This project aims to build a model capable of predicting the identity of a twitter user from their twitter. 

_Before proceeding I would raise the minor caveat that identity here is defined as male, female, or a brand. In some of the code snippets gender is used in place of identity because of how the column was labelled in the data._

## Output Key
Label_0 = Brand 

Label_1 = Female

Label_2 = Male


## Base model
Base model is the mult [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased)
{"license": "apache-2.0"}
transformers pytorch distilbert text-classification license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

# Model Description

This project aims to build a model capable of predicting the identity of a twitter user from their twitter. 

_Before proceeding I would raise the minor caveat that identity here is defined as male, female, or a brand. In some of the code snippets gender is used in place of identity because of how the column was labelled in the data._

## Output Key
Label_0 = Brand 

Label_1 = Female

Label_2 = Male


## Base model
Base model is the mult distilbert-base-multilingual-cased
# Model Description

This project aims to build a model capable of predicting the identity of a twitter user from their twitter. 

_Before proceeding I would raise the minor caveat that identity here is defined as male, female, or a brand. In some of the code snippets gender is used in place of identity because of how the column was labelled in the data._ ## Output Key
Label_0 = Brand 

Label_1 = Female

Label_2 = Male ## Base model
Base model is the mult distilbert-base-multilingual-cased
TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # Model Description

This project aims to build a model capable of predicting the identity of a twitter user from their twitter. 

_Before proceeding I would raise the minor caveat that identity here is defined as male, female, or a brand. In some of the code snippets gender is used in place of identity because of how the column was labelled in the data._ ## Output Key
Label_0 = Brand 

Label_1 = Female

Label_2 = Male ## Base model
Base model is the mult distilbert-base-multilingual-cased
TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# Model Description

This project aims to build a model capable of predicting the identity of a twitter user from their twitter. 

_Before proceeding I would raise the minor caveat that identity here is defined as male, female, or a brand. In some of the code snippets gender is used in place of identity because of how the column was labelled in the data._## Output Key
Label_0 = Brand 

Label_1 = Female

Label_2 = Male## Base model
Base model is the mult distilbert-base-multilingual-cased