update model card README.md

README.md

@@ -1,3 +1,70 @@
 ---
-license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: fine-tuned-arabert-ned-latest
+  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. -->
+
+# fine-tuned-arabert-ned-latest
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1399
+- Accuracy: 0.9741
+- Precision: 0.9789
+- Recall: 0.9818
+- F1: 0.9803
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1337        | 1.0   | 56232  | 0.1134          | 0.9716   | 0.9761    | 0.9809 | 0.9785 |
+| 0.1031        | 2.0   | 112464 | 0.1135          | 0.9742   | 0.9765    | 0.9846 | 0.9805 |
+| 0.0916        | 3.0   | 168696 | 0.1060          | 0.9745   | 0.9791    | 0.9822 | 0.9807 |
+| 0.0812        | 4.0   | 224928 | 0.1138          | 0.9733   | 0.9787    | 0.9808 | 0.9798 |
+| 0.076         | 5.0   | 281160 | 0.1277          | 0.9745   | 0.9782    | 0.9832 | 0.9807 |
+| 0.0676        | 6.0   | 337392 | 0.1399          | 0.9741   | 0.9789    | 0.9818 | 0.9803 |
+
+
+### Framework versions
+
+- Transformers 4.19.2
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1