readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  model-index:
  - name: distilbert-magazine-classifier
    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-magazine-classifier
  
  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8377
  - Precision: 0.25
  - Recall: 0.125
  - Fscore: 0.1667
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 0.1779        | 1.0   | 2    | 1.7584          | 0.2222    | 0.3333 | 0.2667 |
  | 0.1635        | 2.0   | 4    | 1.7585          | 0.25      | 0.125  | 0.1667 |
  | 0.1405        | 3.0   | 6    | 1.8377          | 0.25      | 0.125  | 0.1667 |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  