readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-fin
    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. -->
  
  # bert-base-uncased-finetuned-fin
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4873
  - Accuracy: 0.8793
  - F1: 0.8829
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.5965        | 1.0   | 134  | 0.3922          | 0.8297   | 0.8318 |
  | 0.305         | 2.0   | 268  | 0.3597          | 0.8587   | 0.8632 |
  | 0.2086        | 3.0   | 402  | 0.3483          | 0.8625   | 0.8647 |
  | 0.1618        | 4.0   | 536  | 0.4029          | 0.8634   | 0.8683 |
  | 0.1409        | 5.0   | 670  | 0.4214          | 0.8728   | 0.8771 |
  | 0.1252        | 6.0   | 804  | 0.4305          | 0.8709   | 0.8751 |
  | 0.1204        | 7.0   | 938  | 0.4691          | 0.8653   | 0.8685 |
  | 0.1111        | 8.0   | 1072 | 0.4688          | 0.8737   | 0.8767 |
  | 0.1089        | 9.0   | 1206 | 0.4678          | 0.8746   | 0.8779 |
  | 0.1017        | 10.0  | 1340 | 0.4851          | 0.8756   | 0.8790 |
  | 0.1021        | 11.0  | 1474 | 0.4844          | 0.8784   | 0.8823 |
  | 0.0956        | 12.0  | 1608 | 0.4873          | 0.8793   | 0.8829 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  