update model card README.md

README.md

@@ -1,3 +1,67 @@
 ---
-pipeline_tag: text-classification
----
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: MALWARE-URL-DETECT
+  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. -->
+
+# MALWARE-URL-DETECT
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2122
+- Accuracy: 0.945
+- Precision: 0.9611
+- Recall: 0.9287
+- F1: 0.9446
+
+## 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: 5e-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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 63   | 0.2153          | 0.921    | 0.9953    | 0.8475 | 0.9155 |
+| No log        | 2.0   | 126  | 0.1927          | 0.946    | 0.9669    | 0.9248 | 0.9453 |
+| No log        | 3.0   | 189  | 0.2122          | 0.945    | 0.9611    | 0.9287 | 0.9446 |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3