readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  - precision
  - recall
  model-index:
  - name: bert-bert-cased-first512-Conflict
    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
  
  `conv_text = '\n'.join([utt.text for utt in conv.get_chronological_utterance_list()])`
  
  
  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: 0.6932
  - F1: 0.6667
  - Accuracy: 0.5
  - Precision: 0.5
  - Recall: 1.0
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
  | 0.7098        | 1.0   | 685  | 0.6945          | 0.0    | 0.5      | 0.0       | 0.0    |
  | 0.7046        | 2.0   | 1370 | 0.6997          | 0.6667 | 0.5      | 0.5       | 1.0    |
  | 0.7013        | 3.0   | 2055 | 0.6949          | 0.6667 | 0.5      | 0.5       | 1.0    |
  | 0.7027        | 4.0   | 2740 | 0.6931          | 0.6667 | 0.5      | 0.5       | 1.0    |
  | 0.702         | 5.0   | 3425 | 0.6932          | 0.6667 | 0.5      | 0.5       | 1.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  