Upload README.md

README.md

@@ -8,27 +8,15 @@ library_name: transformers
 pipeline_tag: text-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.
-
-## How to use
-
-You can use the model with the following code.
+## Name
+Vishwa Patel
 
-```python
-from transformers import BertForSequenceClassification, BertTokenizer, TextClassificationPipeline
+## Project
+Toxic Comment Classification
 
-model_path = "JungleLee/bert-toxic-comment-classification"
-tokenizer = BertTokenizer.from_pretrained(model_path)
-model = BertForSequenceClassification.from_pretrained(model_path, num_labels=2)
+## 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.
 
-pipeline = TextClassificationPipeline(model=model, tokenizer=tokenizer)
-print(pipeline("You're a fucking nerd."))
-```
 
 ## 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.
-
-## Evaluation results
-
-The model achieves 0.95 AUC in a 1500 rows held-out test set.