metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - sibyl
datasets:
  - dbpedia_14
metrics:
  - accuracy
base_model: bert-base-uncased
model-index:
  - name: bert-base-uncased-dbpedia_14
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: dbpedia_14
          type: dbpedia_14
          args: dbpedia_14
        metrics:
          - type: accuracy
            value: 0.9902857142857143
            name: Accuracy

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