readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: SAE-bert-base-uncased
    results: []
  widget:
  - text: "Wind [MASK] was detected coming from the car door closure system."
    example_title: "Closure system"
   
  ---
  
  <!-- 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. -->
  
  # SAE-bert-base-uncased
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [jgammack/SAE-door-abstracts](https://huggingface.co/datasets/jgammack/SAE-door-abstracts) dataset.
  
  It achieves the following results on the evaluation set:
  - Loss: 2.1256
  
  ## 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: 7
  - eval_batch_size: 7
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.5967        | 1.0   | 80   | 2.3409          |
  | 2.4881        | 2.0   | 160  | 2.2707          |
  | 2.3567        | 3.0   | 240  | 2.3134          |
  | 2.3413        | 4.0   | 320  | 2.2592          |
  | 2.3006        | 5.0   | 400  | 2.2351          |
  | 2.2568        | 6.0   | 480  | 2.2556          |
  | 2.2303        | 7.0   | 560  | 2.2546          |
  | 2.1892        | 8.0   | 640  | 2.1868          |
  | 2.1851        | 9.0   | 720  | 2.2073          |
  | 2.1738        | 10.0  | 800  | 2.1344          |
  | 2.1673        | 11.0  | 880  | 2.1927          |
  | 2.1518        | 12.0  | 960  | 2.1844          |
  | 2.1142        | 13.0  | 1040 | 2.1466          |
  | 2.1343        | 14.0  | 1120 | 2.2024          |
  | 2.1332        | 15.0  | 1200 | 2.1035          |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  