---
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