readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model_index:
    name: bert-base-uncased-sst2-membership-attack
  ---
  
  <!-- 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-uncased-sst2-membership-attack
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unkown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6296
  - Accuracy: 0.8681
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.6921        | 1.0   | 3813  | 0.6263          | 0.8360   |
  | 0.6916        | 2.0   | 7626  | 0.6296          | 0.8681   |
  | 0.6904        | 3.0   | 11439 | 0.6105          | 0.8406   |
  | 0.6886        | 4.0   | 15252 | 0.6192          | 0.8200   |
  | 0.6845        | 5.0   | 19065 | 0.6250          | 0.7798   |
  
  
  ### Framework versions
  
  - Transformers 4.9.2
  - Pytorch 1.8.1
  - Datasets 1.11.0
  - Tokenizers 0.10.1
  