readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-base-uncased_token_itr0_0.0001_all_01_03_2022-14_21_25
    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_token_itr0_0.0001_all_01_03_2022-14_21_25
  
  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: 0.2698
  - Precision: 0.3321
  - Recall: 0.5265
  - F1: 0.4073
  - Accuracy: 0.8942
  
  ## 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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 30   | 0.3314          | 0.1627    | 0.3746 | 0.2269 | 0.8419   |
  | No log        | 2.0   | 60   | 0.2957          | 0.2887    | 0.4841 | 0.3617 | 0.8592   |
  | No log        | 3.0   | 90   | 0.2905          | 0.2429    | 0.5141 | 0.3299 | 0.8651   |
  | No log        | 4.0   | 120  | 0.2759          | 0.3137    | 0.5565 | 0.4013 | 0.8787   |
  | No log        | 5.0   | 150  | 0.2977          | 0.3116    | 0.5565 | 0.3995 | 0.8796   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.1+cu113
  - Datasets 1.18.0
  - Tokenizers 0.10.3
  