readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: distilbert-base-uncased_research_articles_multilabel
    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_research_articles_multilabel
  
  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: 0.1956
  - F1: 0.8395
  - Roc Auc: 0.8909
  - Accuracy: 0.6977
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | 0.3043        | 1.0   | 263  | 0.2199          | 0.8198 | 0.8686  | 0.6829   |
  | 0.2037        | 2.0   | 526  | 0.1988          | 0.8355 | 0.8845  | 0.7010   |
  | 0.1756        | 3.0   | 789  | 0.1956          | 0.8395 | 0.8909  | 0.6977   |
  | 0.1579        | 4.0   | 1052 | 0.1964          | 0.8371 | 0.8902  | 0.6919   |
  | 0.1461        | 5.0   | 1315 | 0.1991          | 0.8353 | 0.8874  | 0.6953   |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  