readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-detests-02-11-2022
    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-finetuned-detests-02-11-2022
  
  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: 1.0794
  - F1: 0.5455
  
  ## 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: 2e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.014         | 0.64  | 25   | 0.6229          | 0.5536 |
  | 0.0698        | 1.28  | 50   | 0.6996          | 0.5907 |
  | 0.0173        | 1.92  | 75   | 0.7531          | 0.5882 |
  | 0.0032        | 2.56  | 100  | 0.8054          | 0.4928 |
  | 0.0087        | 3.21  | 125  | 0.9557          | 0.5735 |
  | 0.0028        | 3.85  | 150  | 0.8859          | 0.5352 |
  | 0.013         | 4.49  | 175  | 0.9674          | 0.5536 |
  | 0.0031        | 5.13  | 200  | 0.9073          | 0.5691 |
  | 0.0032        | 5.77  | 225  | 0.9253          | 0.5439 |
  | 0.0483        | 6.41  | 250  | 0.9705          | 0.5837 |
  | 0.0323        | 7.05  | 275  | 1.0368          | 0.5824 |
  | 0.0019        | 7.69  | 300  | 1.0221          | 0.5520 |
  | 0.0256        | 8.33  | 325  | 1.0419          | 0.5523 |
  | 0.0319        | 8.97  | 350  | 1.0764          | 0.5425 |
  | 0.0125        | 9.62  | 375  | 1.0794          | 0.5455 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  