Update README.md

README.md

@@ -1,57 +1,19 @@
 ---
 license: mit
-tags:
-- generated_from_keras_callback
 model-index:
 - name: indobert-abusive-language-classifier
   results: []
+tags:
+- text-classification
+- bert
+- indobert
 ---
 
-<!-- This model card has been generated automatically according to the information Keras had access to. You should
-probably proofread and complete it, then remove this comment. -->
-
 # indobert-abusive-language-classifier
 
-This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Train Loss: 0.1777
-- Train Sparse Categorical Accuracy: 0.9318
-- Validation Loss: 0.2693
-- Validation Sparse Categorical Accuracy: 0.9017
-- Epoch: 2
 
 ## Model description
 
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
-- training_precision: float32
-
-### Training results
-
-| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
-|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
-| 0.4750     | 0.7658                            | 0.3018          | 0.8709                                 | 0     |
-| 0.2758     | 0.8871                            | 0.2713          | 0.8804                                 | 1     |
-| 0.1777     | 0.9318                            | 0.2693          | 0.9017                                 | 2     |
-
-
-### Framework versions
+This model is an abusive language classifier for Bahasa Indonesia based on [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased).
+It was trained on a modified [Multi-label Hate Speech and Abusive Language Detection](https://github.com/okkyibrohim/id-multi-label-hate-speech-and-abusive-language-detection) dataset and achieves an evaluation accuracy of 90.17%.
 
-- Transformers 4.26.1
-- TensorFlow 2.11.0
-- Datasets 2.10.1
-- Tokenizers 0.13.2