readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  - precision
  - recall
  model-index:
  - name: bert-bert-cased-first512-Conflict-SEP
    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-bert-cased-first512-Conflict-SEP
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6806
  - F1: 0.6088
  - Accuracy: 0.5914
  - Precision: 0.5839
  - Recall: 0.6360
  
  ## 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
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
  | 0.7027        | 1.0   | 685  | 0.6956          | 0.6018 | 0.5365   | 0.5275    | 0.7003 |
  | 0.7009        | 2.0   | 1370 | 0.6986          | 0.6667 | 0.5      | 0.5       | 1.0    |
  | 0.7052        | 3.0   | 2055 | 0.6983          | 0.6667 | 0.5      | 0.5       | 1.0    |
  | 0.6987        | 4.0   | 2740 | 0.6830          | 0.5235 | 0.5636   | 0.5764    | 0.4795 |
  | 0.6761        | 5.0   | 3425 | 0.6806          | 0.6088 | 0.5914   | 0.5839    | 0.6360 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  