update model card README.md

README.md

@@ -0,0 +1,83 @@
+---
+tags:
+- generated_from_trainer
+datasets:
+- emotone_ar
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-arabic-finetuned-emotion
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotone_ar
+      type: emotone_ar
+      config: default
+      split: train[:90%]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7266401590457257
+    - name: F1
+      type: f1
+      value: 0.7258317874418239
+---
+
+<!-- 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. -->
+
+# bert-base-arabic-finetuned-emotion
+
+This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9079
+- Accuracy: 0.7266
+- F1: 0.7258
+
+## 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: 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: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.2471        | 1.0   | 142  | 0.8635          | 0.7078   | 0.6951 |
+| 0.7906        | 2.0   | 284  | 0.8124          | 0.7266   | 0.7202 |
+| 0.5983        | 3.0   | 426  | 0.8331          | 0.7336   | 0.7262 |
+| 0.4615        | 4.0   | 568  | 0.8542          | 0.7266   | 0.7240 |
+| 0.3573        | 5.0   | 710  | 0.8924          | 0.7286   | 0.7274 |
+| 0.2969        | 6.0   | 852  | 0.9079          | 0.7266   | 0.7258 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Datasets 2.8.0
+- Tokenizers 0.13.2