readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: bert_base_uncased_itr0_0.0001_all_01_03_2022-14_08_15
    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_itr0_0.0001_all_01_03_2022-14_08_15
  
  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: 0.7632
  - Accuracy: 0.8263
  - F1: 0.8871
  - Precision: 0.8551
  - Recall: 0.9215
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - 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 | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | No log        | 1.0   | 390  | 0.3986          | 0.8305   | 0.8903 | 0.8868    | 0.8938 |
  | 0.4561        | 2.0   | 780  | 0.4018          | 0.8439   | 0.9009 | 0.8805    | 0.9223 |
  | 0.3111        | 3.0   | 1170 | 0.4306          | 0.8354   | 0.8924 | 0.8974    | 0.8875 |
  | 0.1739        | 4.0   | 1560 | 0.5499          | 0.8378   | 0.9002 | 0.8547    | 0.9509 |
  | 0.1739        | 5.0   | 1950 | 0.6223          | 0.85     | 0.9052 | 0.8814    | 0.9303 |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  