Update README.md

README.md

@@ -7,16 +7,10 @@ language:
 pipeline_tag: text-classification
 ---
 
-## About the model
-It is a Turkish bert-based model created to determine the types of bullying that people use against each other in social media.
-Included classes;
+# About the model
+This model is designed for text classification, specifically for identifying offensive content in Turkish text. The model classifies text into five categories: INSULT, OTHER, PROFANITY, RACIST, and SEXIST.
 
-- Nötr
-- Kızdırma/Hakaret
-- Cinsiyetçilik
-- Irkçılık
-
-3388 tweets were used in the training of the model. Accordingly, the success rates in education are as follows;
+## Model Metrics
 
 |        | INSULT | OTHER | PROFANITY | RACIST | SEXIST |
 | ------ | ------  | ------ | ------  | ------ | ------ |
@@ -29,6 +23,15 @@ Included classes;
 - Precision:  0.9570284225256961
 - Accuracy:  0.956
 
+## Training Information
+- Device : macOS 14.5 23F79 arm64 | GPU: Apple M2 Max | Memory: 5840MiB / 32768MiB 
+- Training completed in 0:22:54 (hh:mm:ss)
+- Optimizer: AdamW
+- learning_rate: 2e-5 
+- eps: 1e-8 
+- epochs: 10
+- Batch size: 64
+
 ## Dependency
 pip install torch torchvision torchaudio
 pip install tf-keras