readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess2
    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. -->
  
  # covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess2
  
  This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5816
  - Accuracy: 0.0901
  
  ## 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: 1.4275469935864394e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 40
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.8511        | 1.0   | 700  | 0.6372          | 0.1478   |
  | 0.6146        | 2.0   | 1400 | 0.5816          | 0.0901   |
  | 0.365         | 3.0   | 2100 | 0.6170          | 0.0749   |
  | 0.2686        | 4.0   | 2800 | 0.7259          | 0.0688   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu102
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  