readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  - sibyl
  datasets:
  - dbpedia_14
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-dbpedia_14
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: dbpedia_14
        type: dbpedia_14
        args: dbpedia_14
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9902857142857143
  ---
  
  <!-- 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. -->
  
  # bert-base-uncased-dbpedia_14
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the dbpedia_14 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0547
  - Accuracy: 0.9903
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 34650
  - training_steps: 346500
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.7757        | 0.03  | 2000  | 0.2732          | 0.9880   |
  | 0.1002        | 0.06  | 4000  | 0.0620          | 0.9891   |
  | 0.0547        | 0.09  | 6000  | 0.0723          | 0.9879   |
  | 0.0558        | 0.12  | 8000  | 0.0678          | 0.9875   |
  | 0.0534        | 0.14  | 10000 | 0.0554          | 0.9896   |
  | 0.0632        | 0.17  | 12000 | 0.0670          | 0.9888   |
  | 0.0612        | 0.2   | 14000 | 0.0733          | 0.9873   |
  | 0.0667        | 0.23  | 16000 | 0.0623          | 0.9896   |
  | 0.0636        | 0.26  | 18000 | 0.0836          | 0.9868   |
  | 0.0705        | 0.29  | 20000 | 0.0776          | 0.9855   |
  | 0.0726        | 0.32  | 22000 | 0.0805          | 0.9861   |
  | 0.0778        | 0.35  | 24000 | 0.0713          | 0.9870   |
  | 0.0713        | 0.38  | 26000 | 0.1277          | 0.9805   |
  | 0.0965        | 0.4   | 28000 | 0.0810          | 0.9855   |
  | 0.0881        | 0.43  | 30000 | 0.0910          | 0.985    |
  
  
  ### Framework versions
  
  - Transformers 4.10.2
  - Pytorch 1.7.1
  - Datasets 1.6.1
  - Tokenizers 0.10.3
  