Update README.md

RoBERTa Fast Tokenizer + Sequence Classifier

-Make sure to use/ convert inputs into small characters before sending or testing the model for accurate predition.

Details:
Epoch - 3
Accuracy - 0.85
F1 - 0.85
Precision - 0.84
Recall - 0.86
0.92

t-SNE Visualization:

Conducted by:
Jordan Limwell C. Marcelo

README.md

@@ -5,6 +5,10 @@ metrics:
 - accuracy
 pipeline_tag: text-classification
 library_name: transformers
+datasets:
+- syke9p3/multilabel-tagalog-hate-speech
+- mapsoriano/2016_2022_hate_speech_filipino
+- mginoben/tagalog-profanity-dataset
 ---
 ## Model Card
 - **Task**: Text Classification
@@ -18,8 +22,7 @@ tags:
   - "text-classification"
   - "hate-speech"
   - "nlp"
-dataset: "various datasets"
-license: "MIT"
+license: ""
 model-index:
   - name: "default"
     task: "text-classification"