readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: facility-classifier
    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. -->
  
  # facility-classifier
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4422
  - Accuracy: 0.7872
  - F1: 0.7854
  
  ## 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: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.671         | 1.0   | 12   | 0.6529          | 0.6596   | 0.6441 |
  | 0.5845        | 2.0   | 24   | 0.5722          | 0.7447   | 0.7461 |
  | 0.4902        | 3.0   | 36   | 0.5091          | 0.7447   | 0.7461 |
  | 0.378         | 4.0   | 48   | 0.4797          | 0.7660   | 0.7670 |
  | 0.354         | 5.0   | 60   | 0.4487          | 0.8085   | 0.8029 |
  | 0.2865        | 6.0   | 72   | 0.4422          | 0.7872   | 0.7854 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  