update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- xnli
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: xnli
+      type: xnli
+      config: ar
+      split: train
+      args: ar
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.767065868263473
+    - name: F1
+      type: f1
+      value: 0.767539058869847
+---
+
+<!-- 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-camelbert-msa-sixteenth-xnli-finetuned
+
+This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the xnli dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5796
+- Accuracy: 0.7671
+- F1: 0.7675
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.5804        | 1.0   | 12271 | 0.5796          | 0.7671   | 0.7675 |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.1+cu117
+- Datasets 2.8.0
+- Tokenizers 0.13.2