Update model card

README.md

@@ -1,3 +1,54 @@
----
-license: mit
----
+---
+language:
+- en
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: qnli
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE QNLI
+      type: glue
+      args: qnli
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9077429983525536
+---
+
+# bert-base-cased-qnli
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE QNLI dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2835
+- Accuracy: 0.9077
+
+## Model description
+Please refer to [this repository](https://huggingface.co/google-bert/bert-base-cased).
+
+## Intended uses
+This model is for the artifact evaluation of the paper "SHAFT: Secure, Handy, Accurate, and Fast Transformer Inference."
+
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1