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README.md
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---
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language:
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- en
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license: apache-2.0
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base_model: bert-base-cased
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- matthews_correlation
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model-index:
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- name: cola
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: GLUE COLA
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type: glue
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args: cola
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metrics:
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- name: Matthews Correlation
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type: matthews_correlation
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value: 0.5778184033685675
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---
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# bert-base-cased-cola
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the GLUE COLA dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5006
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- Matthews Correlation: 0.5778
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## Model description
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Please refer to [this repository](https://huggingface.co/google-bert/bert-base-cased).
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## Intended uses
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This model is for the artifact evaluation of the paper "SHAFT: Secure, Handy, Accurate, and Fast Transformer Inference."
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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### Framework versions
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- Transformers 4.42.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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