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metadata
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

bert-base-uncased-dbpedia_14

This model is a fine-tuned version of 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