metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding60model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.944078947368421

distilbert_agnews_padding60model

This model is a fine-tuned version of distilbert-base-uncased on the ag_news dataset. It achieves the following results on the evaluation set:

Loss: 0.6521
Accuracy: 0.9441

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1838	1.0	7500	0.1831	0.9422
0.1417	2.0	15000	0.2010	0.9418
0.1226	3.0	22500	0.2138	0.9476
0.0872	4.0	30000	0.2581	0.9426
0.0614	5.0	37500	0.2946	0.9421
0.0432	6.0	45000	0.3639	0.9420
0.0384	7.0	52500	0.4363	0.9382
0.0297	8.0	60000	0.3892	0.9436
0.0206	9.0	67500	0.4465	0.9408
0.0126	10.0	75000	0.4713	0.9414
0.0146	11.0	82500	0.4982	0.9432
0.0143	12.0	90000	0.5465	0.9392
0.0092	13.0	97500	0.5421	0.9382
0.0055	14.0	105000	0.5625	0.9404
0.0025	15.0	112500	0.6237	0.9416
0.0014	16.0	120000	0.5890	0.9434
0.0065	17.0	127500	0.6210	0.9458
0.003	18.0	135000	0.6399	0.9439
0.0011	19.0	142500	0.6500	0.9458
0.0006	20.0	150000	0.6521	0.9441

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3