readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: Heritage-in-the-Digital-Age-expression-comparison
    results: []
  widget:
  - text: "people buying sweets at the market. [SEP] saint nicholas festival market"
    example_title: "Caption vs Title"
  ---
  
  <!-- 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. -->
  
  # Heritage-in-the-Digital-Age-expression-comparison
  
  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: 0.5281
  - Accuracy: 0.7709
  
  ## 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: 15
  - eval_batch_size: 15
  - 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 | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 136  | 0.5281          | 0.7709   |
  | No log        | 2.0   | 272  | 0.5288          | 0.7709   |
  | No log        | 3.0   | 408  | 0.5311          | 0.7629   |
  | 0.4623        | 4.0   | 544  | 0.5814          | 0.7595   |
  | 0.4623        | 5.0   | 680  | 0.5764          | 0.7549   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  