readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-finetuned-vr-comfort-2125
    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-vr-comfort-2125
  
  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: 1.0440
  - Accuracy: 0.8431
  - F1: 0.8437
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.7159        | 1.0   | 157  | 0.6408          | 0.7401   | 0.6612 |
  | 0.5559        | 2.0   | 314  | 0.5362          | 0.7952   | 0.7684 |
  | 0.362         | 3.0   | 471  | 0.5135          | 0.8204   | 0.8132 |
  | 0.1918        | 4.0   | 628  | 0.6109          | 0.8407   | 0.8388 |
  | 0.1192        | 5.0   | 785  | 0.6947          | 0.8347   | 0.8316 |
  | 0.0661        | 6.0   | 942  | 0.7843          | 0.8455   | 0.8467 |
  | 0.0507        | 7.0   | 1099 | 0.9312          | 0.8168   | 0.8271 |
  | 0.0406        | 8.0   | 1256 | 0.8616          | 0.8467   | 0.8488 |
  | 0.0268        | 9.0   | 1413 | 0.8403          | 0.8443   | 0.8478 |
  | 0.0251        | 10.0  | 1570 | 0.8662          | 0.8467   | 0.8472 |
  | 0.0188        | 11.0  | 1727 | 0.9418          | 0.8563   | 0.8530 |
  | 0.0195        | 12.0  | 1884 | 0.9541          | 0.8479   | 0.8469 |
  | 0.0172        | 13.0  | 2041 | 0.9372          | 0.8407   | 0.8413 |
  | 0.0142        | 14.0  | 2198 | 0.9883          | 0.8491   | 0.8469 |
  | 0.0156        | 15.0  | 2355 | 1.0150          | 0.8419   | 0.8428 |
  | 0.0138        | 16.0  | 2512 | 1.0035          | 0.8479   | 0.8466 |
  | 0.013         | 17.0  | 2669 | 1.0909          | 0.8299   | 0.8355 |
  | 0.0115        | 18.0  | 2826 | 1.0278          | 0.8515   | 0.8490 |
  | 0.0107        | 19.0  | 2983 | 1.0419          | 0.8431   | 0.8437 |
  | 0.0101        | 20.0  | 3140 | 1.0440          | 0.8431   | 0.8437 |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.11.0
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  