Update README.md

README.md

@@ -17,17 +17,16 @@ Try out "ScamLLM" using the Inference API. Our model classifies prompts with "La
 ## Dataset Details
 
 The dataset utilized for training this model has been created using malicious prompts generated by GPT-4. 
-Due to ethical concerns, our dataset is currently available only upon request.
+Due to being active vulnerabilities under review, our dataset of malicious prompts is available only upon request at this stage, with plans for a public release scheduled for May 2024. 
 
 ## Training Details
 
 The model was trained using RobertaForSequenceClassification.from_pretrained. 
-In this process, both the model and tokenizer pertinent to the RoBERTa-base were employed. 
-We trained this model for 10 epochs, setting a learning rate to 2e-5, and used AdamW Optimizer. 
+In this process, both the model and tokenizer pertinent to the RoBERTa-base were employed and trained for 10 epochs (learning rate to 2e-5 and used AdamW Optimizer). 
 
 ## Inference
 
-There are multiple ways to use this model. The simplest way to use is with pipeline "text-classification"
+There are multiple ways to test this model, with the simplest being to use the Inference API, as well as with the pipeline "text-classification" as below:
 
 ```python
 from transformers import pipeline
@@ -36,7 +35,3 @@ prompt = ["Your Sample Sentence or Prompt...."]
 model_outputs = classifier(prompt)
 print(model_outputs[0])
 ```
-
-### Results
-
-Achieved an accuracy of 94% with an F1-score of 0.94, on test sets.