readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: final_five_class_classification
    results: []
  ---
  
  <!-- 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. -->
  
  # final_five_class_classification
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1000
  - F1: 0.9566
  - Roc Auc: 0.9664
  - Accuracy: 0.875
  
  ## 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
  - 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 | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | No log        | 1.0   | 250  | 0.2560          | 0.8761 | 0.9004  | 0.665    |
  | 0.3126        | 2.0   | 500  | 0.2082          | 0.8966 | 0.9177  | 0.7025   |
  | 0.3126        | 3.0   | 750  | 0.1879          | 0.9024 | 0.9254  | 0.705    |
  | 0.2165        | 4.0   | 1000 | 0.1654          | 0.9166 | 0.9348  | 0.755    |
  | 0.2165        | 5.0   | 1250 | 0.1403          | 0.9346 | 0.9500  | 0.7975   |
  | 0.1619        | 6.0   | 1500 | 0.1288          | 0.9394 | 0.9523  | 0.815    |
  | 0.1619        | 7.0   | 1750 | 0.1112          | 0.9515 | 0.9614  | 0.855    |
  | 0.1161        | 8.0   | 2000 | 0.1112          | 0.9492 | 0.9585  | 0.8575   |
  | 0.1161        | 9.0   | 2250 | 0.1029          | 0.9536 | 0.9631  | 0.8725   |
  | 0.086         | 10.0  | 2500 | 0.1000          | 0.9566 | 0.9664  | 0.875    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.1+cpu
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  