update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- sem_eval_2018_task_1
+metrics:
+- f1
+- accuracy
+model-index:
+- name: arabert-emotions-classification
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sem_eval_2018_task_1
+      type: sem_eval_2018_task_1
+      config: subtask5.arabic
+      split: validation
+      args: subtask5.arabic
+    metrics:
+    - name: F1
+      type: f1
+      value: 0.7189952904238618
+    - name: Accuracy
+      type: accuracy
+      value: 0.2717948717948718
+---
+
+<!-- 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. -->
+
+# arabert-emotions-classification
+
+This model is a fine-tuned version of [aubmindlab/bert-large-arabertv02-twitter](https://huggingface.co/aubmindlab/bert-large-arabertv02-twitter) on the sem_eval_2018_task_1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2636
+- F1: 0.7190
+- Roc Auc: 0.8061
+- Accuracy: 0.2718
+
+## 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: 20
+- eval_batch_size: 20
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| No log        | 1.0   | 114  | 0.3055          | 0.6653 | 0.7674  | 0.2462   |
+| No log        | 2.0   | 228  | 0.2776          | 0.6987 | 0.7887  | 0.2701   |
+| No log        | 3.0   | 342  | 0.2680          | 0.7062 | 0.7943  | 0.2769   |
+| No log        | 4.0   | 456  | 0.2644          | 0.7140 | 0.8032  | 0.2718   |
+| 0.2701        | 5.0   | 570  | 0.2636          | 0.7190 | 0.8061  | 0.2718   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3