readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-subreddit_classification
    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-subreddit_classification
  
  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: 0.2958
  - Accuracy: 0.91
  
  ## 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: 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.4142        | 0.6   | 30   | 1.2653          | 0.45     |
  | 0.9856        | 1.2   | 60   | 0.7754          | 0.87     |
  | 0.5056        | 1.8   | 90   | 0.4413          | 0.9      |
  | 0.2248        | 2.4   | 120  | 0.2984          | 0.92     |
  | 0.1352        | 3.0   | 150  | 0.3265          | 0.89     |
  | 0.0856        | 3.6   | 180  | 0.2958          | 0.91     |
  | 0.0715        | 4.2   | 210  | 0.2611          | 0.92     |
  | 0.0615        | 4.8   | 240  | 0.2738          | 0.93     |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.13.0+cpu
  - Datasets 2.8.0
  - Tokenizers 0.12.1
  