update model card README.md

README.md

@@ -1,3 +1,67 @@
 ---
-license: other
+license: cc-by-sa-4.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: roberta-tagalog-profanity-classifier
+  results: []
 ---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# roberta-tagalog-profanity-classifier
+
+This model is a fine-tuned version of [jcblaise/roberta-tagalog-base](https://huggingface.co/jcblaise/roberta-tagalog-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2897
+- Accuracy: 0.8855
+- Precision: 0.8864
+- Recall: 0.9126
+- F1: 0.8993
+
+## 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:
+- learning_rate: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 174  | 0.3082          | 0.8790   | 0.8900    | 0.8946 | 0.8923 |
+| No log        | 2.0   | 348  | 0.2861          | 0.8848   | 0.8902    | 0.9062 | 0.8981 |
+| 0.2991        | 3.0   | 522  | 0.2897          | 0.8855   | 0.8864    | 0.9126 | 0.8993 |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3