
## Name
Vishwa Patel

## Project
Toxic Comment Classification

## Model description
This model is a fine-tuned version of the [bert-base-uncased](https://huggingface.co/transformers/model_doc/bert.html) model to classify toxic comments.


## Training data
The training data comes from this [Kaggle competition](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/data). We use 90% of the `train.csv` data to train the model.

{"language": ["en"], "license": "afl-3.0", "library_name": "transformers", "metrics": ["accuracy"], "pipeline_tag": "text-classification"}
transformers pytorch bert text-classification en license:afl-3.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #en #license-afl-3.0 #autotrain_compatible #endpoints_compatible #region-us 


## Name
Vishwa Patel

## Project
Toxic Comment Classification

## Model description
This model is a fine-tuned version of the bert-base-uncased model to classify toxic comments.


## Training data
The training data comes from this Kaggle competition. We use 90% of the 'URL' data to train the model.

## Name
Vishwa Patel ## Project
Toxic Comment Classification ## Model description
This model is a fine-tuned version of the bert-base-uncased model to classify toxic comments. ## Training data
The training data comes from this Kaggle competition. We use 90% of the 'URL' data to train the model.
TAGS
#transformers #pytorch #bert #text-classification #en #license-afl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## Name
Vishwa Patel ## Project
Toxic Comment Classification ## Model description
This model is a fine-tuned version of the bert-base-uncased model to classify toxic comments. ## Training data
The training data comes from this Kaggle competition. We use 90% of the 'URL' data to train the model.
TAGS
#transformers #pytorch #bert #text-classification #en #license-afl-3.0 #autotrain_compatible #endpoints_compatible #region-us 
## Name
Vishwa Patel## Project
Toxic Comment Classification## Model description
This model is a fine-tuned version of the bert-base-uncased model to classify toxic comments.## Training data
The training data comes from this Kaggle competition. We use 90% of the 'URL' data to train the model.