readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - eoir_privacy
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer-finetuned-eoir_privacy-longer30
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: eoir_privacy
        type: eoir_privacy
        config: all
        split: train
        args: all
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9490674318507891
      - name: F1
        type: f1
        value: 0.88379705400982
  ---
  
  <!-- 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_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer-finetuned-eoir_privacy-longer30
  
  This model was trained from scratch on the eoir_privacy dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2076
  - Accuracy: 0.9491
  - F1: 0.8838
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 63   | 0.2446          | 0.9426   | 0.8671 |
  | No log        | 2.0   | 126  | 0.2306          | 0.9412   | 0.8629 |
  | No log        | 3.0   | 189  | 0.2637          | 0.9448   | 0.8679 |
  | No log        | 4.0   | 252  | 0.2375          | 0.9455   | 0.8758 |
  | No log        | 5.0   | 315  | 0.2423          | 0.9440   | 0.8687 |
  | No log        | 6.0   | 378  | 0.2571          | 0.9455   | 0.8676 |
  | No log        | 7.0   | 441  | 0.2040          | 0.9469   | 0.8799 |
  | 0.0355        | 8.0   | 504  | 0.2096          | 0.9462   | 0.8784 |
  | 0.0355        | 9.0   | 567  | 0.2094          | 0.9448   | 0.8736 |
  | 0.0355        | 10.0  | 630  | 0.2076          | 0.9491   | 0.8838 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  