Update README.md

README.md

@@ -2,6 +2,15 @@
 language:
 - en
 pipeline_tag: text-classification
+license: mit
+metrics:
+- accuracy
+- f1
 ---
-It is a model able to predict toxicity given a history and a response to it. It is created for dialog agents. To use it correctly please use the following schematics: [HST]Hi,how are you?`[END]I am doing fine[ANS] I hope you die.
-Token [HST] initiates the history of the conversation and every pair turn is separeted by [END]. Token [ANS] indicates start of the response to the last utterance. I will update this card, but right now I am developing a bigger proyect with these,so i dont have the time to indicate all the results.
+This model is part of the research presented in "Mitigating Toxicity in Dialogue Agents through Adversarial Reinforcement Learning," a conference paper addressing dialog agent toxicity by mitigating it at three levels: explicit, implicit, and contextual. It is a model capable of predicting toxicity given a history and a response to it. It is designed for dialog agents. To use it correctly, please follow the schematics below:
+
+[HST]Hi, how are you?[END]I am doing fine[ANS]I hope you die.
+
+The token [HST] initiates the history of the conversation, and each turn pair is separated by [END]. The token [ANS] indicates the start of the response to the last utterance. I will update this card, but right now, I am developing a bigger project with these, so I do not have the time to indicate all the results.
+
+The datasets used to train the model were the Dialogue Safety dataset and Bot Adversarial dataset.