readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-large-uncased-finetuned-filtered-0602
    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-large-uncased-finetuned-filtered-0602
  
  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8409
  - Accuracy: 0.1667
  - F1: 0.0476
  
  ## 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: 5e-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
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
  | 1.8331        | 1.0   | 3180  | 1.8054          | 0.1667   | 0.0476 |
  | 1.8158        | 2.0   | 6360  | 1.8196          | 0.1667   | 0.0476 |
  | 1.8088        | 3.0   | 9540  | 1.8059          | 0.1667   | 0.0476 |
  | 1.8072        | 4.0   | 12720 | 1.7996          | 0.1667   | 0.0476 |
  | 1.8182        | 5.0   | 15900 | 1.7962          | 0.1667   | 0.0476 |
  | 1.7993        | 6.0   | 19080 | 1.8622          | 0.1667   | 0.0476 |
  | 1.7963        | 7.0   | 22260 | 1.8378          | 0.1667   | 0.0476 |
  | 1.7956        | 8.0   | 25440 | 1.8419          | 0.1667   | 0.0476 |
  | 1.7913        | 9.0   | 28620 | 1.8406          | 0.1667   | 0.0476 |
  | 1.7948        | 10.0  | 31800 | 1.8409          | 0.1667   | 0.0476 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.0
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  