readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - health_fact
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased-finetuned-health_facts
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: health_fact
        type: health_fact
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.628500823723229
      - name: F1
        type: f1
        value: 0.6544946803476833
  ---
  
  <!-- 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. -->
  
  # distilbert-base-uncased-finetuned-health_facts
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the health_fact dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1227
  - Accuracy: 0.6285
  - F1: 0.6545
  
  ## 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 | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.1367        | 1.0   | 154  | 0.9423          | 0.5560   | 0.6060 |
  | 0.9444        | 2.0   | 308  | 0.9267          | 0.5733   | 0.6170 |
  | 0.8248        | 3.0   | 462  | 0.9483          | 0.5832   | 0.6256 |
  | 0.7213        | 4.0   | 616  | 1.0119          | 0.5815   | 0.6219 |
  | 0.608         | 5.0   | 770  | 1.1227          | 0.6285   | 0.6545 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  