readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: distilbert-base-uncased-finetuned-truthful
    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-truthful
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4660
  - Accuracy: 0.87
  - F1: 0.8697
  
  ## 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: 9.910294163459086e-05
  - train_batch_size: 400
  - eval_batch_size: 400
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 9
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | No log        | 1.0   | 5    | 0.6509          | 0.59     | 0.5780 |
  | No log        | 2.0   | 10   | 0.4950          | 0.77     | 0.7701 |
  | No log        | 3.0   | 15   | 0.4787          | 0.81     | 0.8099 |
  | No log        | 4.0   | 20   | 0.4936          | 0.81     | 0.8096 |
  | No log        | 5.0   | 25   | 0.4443          | 0.82     | 0.82   |
  | No log        | 6.0   | 30   | 0.4547          | 0.85     | 0.8497 |
  | No log        | 7.0   | 35   | 0.4268          | 0.85     | 0.8500 |
  | No log        | 8.0   | 40   | 0.4790          | 0.87     | 0.8697 |
  | No log        | 9.0   | 45   | 0.4660          | 0.87     | 0.8697 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.1
  - Datasets 2.0.0
  - Tokenizers 0.11.0
  