readme: ---
  license: apache-2.0
  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
    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: 0.9476327116212339
      - name: F1
        type: f1
        value: 0.8805237315875615
  ---
  
  <!-- 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
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the eoir_privacy dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1738
  - Accuracy: 0.9476
  - F1: 0.8805
  
  ## 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   | 0.2004          | 0.9261   | 0.8298 |
  | No log        | 2.0   | 126  | 0.2042          | 0.9297   | 0.8435 |
  | No log        | 3.0   | 189  | 0.1888          | 0.9362   | 0.8558 |
  | No log        | 4.0   | 252  | 0.1879          | 0.9383   | 0.8532 |
  | No log        | 5.0   | 315  | 0.1715          | 0.9462   | 0.8788 |
  | No log        | 6.0   | 378  | 0.1761          | 0.9448   | 0.8706 |
  | No log        | 7.0   | 441  | 0.1730          | 0.9455   | 0.8774 |
  | 0.1078        | 8.0   | 504  | 0.1753          | 0.9448   | 0.8772 |
  | 0.1078        | 9.0   | 567  | 0.1721          | 0.9469   | 0.8791 |
  | 0.1078        | 10.0  | 630  | 0.1738          | 0.9476   | 0.8805 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  