metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_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: 0.945

N_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: 0.6714
Accuracy: 0.945

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
0.1829	1.0	7500	0.1828	0.9445
0.1406	2.0	15000	0.1995	0.9436
0.1229	3.0	22500	0.2025	0.9470
0.0893	4.0	30000	0.2578	0.9464
0.0547	5.0	37500	0.3250	0.9392
0.0394	6.0	45000	0.3882	0.9391
0.0368	7.0	52500	0.4054	0.9383
0.0221	8.0	60000	0.4602	0.9396
0.0179	9.0	67500	0.4535	0.9430
0.015	10.0	75000	0.4745	0.9421
0.0177	11.0	82500	0.5035	0.9439
0.0147	12.0	90000	0.4848	0.9436
0.0077	13.0	97500	0.5222	0.9447
0.0039	14.0	105000	0.5591	0.9432
0.0042	15.0	112500	0.5863	0.9433
0.0017	16.0	120000	0.6075	0.9457
0.003	17.0	127500	0.6207	0.9455
0.0017	18.0	135000	0.6482	0.9454
0.0004	19.0	142500	0.6646	0.9457
0.0017	20.0	150000	0.6714	0.945

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3