readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-osdg
    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. -->
  
  # distilbert-base-uncased-finetuned-osdg
  
  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: 1.8193
  - F1 Score: 0.7962
  - Accuracy: 0.8434
  
  ## 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: 5e-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 | F1 Score | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
  | 0.3769        | 1.0   | 1017  | 0.8258          | 0.7729   | 0.8257   |
  | 0.2759        | 2.0   | 2034  | 0.8364          | 0.7773   | 0.8262   |
  | 0.1412        | 3.0   | 3051  | 1.0203          | 0.7833   | 0.8379   |
  | 0.1423        | 4.0   | 4068  | 1.1603          | 0.7683   | 0.8224   |
  | 0.0939        | 5.0   | 5085  | 1.3029          | 0.7843   | 0.8329   |
  | 0.0757        | 6.0   | 6102  | 1.3562          | 0.7931   | 0.8379   |
  | 0.0801        | 7.0   | 7119  | 1.2925          | 0.7840   | 0.8395   |
  | 0.0311        | 8.0   | 8136  | 1.4632          | 0.7750   | 0.8318   |
  | 0.0263        | 9.0   | 9153  | 1.5760          | 0.7843   | 0.8312   |
  | 0.0196        | 10.0  | 10170 | 1.5689          | 0.7890   | 0.8417   |
  | 0.0313        | 11.0  | 11187 | 1.6034          | 0.7909   | 0.8417   |
  | 0.0007        | 12.0  | 12204 | 1.6725          | 0.7889   | 0.8406   |
  | 0.0081        | 13.0  | 13221 | 1.6463          | 0.7911   | 0.8395   |
  | 0.0061        | 14.0  | 14238 | 1.7730          | 0.7861   | 0.8345   |
  | 0.003         | 15.0  | 15255 | 1.8001          | 0.7847   | 0.8379   |
  | 0.0002        | 16.0  | 16272 | 1.7328          | 0.7912   | 0.8434   |
  | 0.0           | 17.0  | 17289 | 1.7914          | 0.8011   | 0.8489   |
  | 0.0009        | 18.0  | 18306 | 1.7772          | 0.7958   | 0.8456   |
  | 0.0           | 19.0  | 19323 | 1.8028          | 0.7958   | 0.8434   |
  | 0.0           | 20.0  | 20340 | 1.8193          | 0.7962   | 0.8434   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  