metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding0model
    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: 0.9464473684210526

distilbert_agnews_padding0model

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: 0.6408
Accuracy: 0.9464

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
0.1774	1.0	7500	0.1995	0.9392
0.1403	2.0	15000	0.1939	0.9447
0.1114	3.0	22500	0.2186	0.9459
0.0741	4.0	30000	0.2832	0.9446
0.0499	5.0	37500	0.3070	0.9408
0.0376	6.0	45000	0.3704	0.9434
0.0341	7.0	52500	0.3999	0.9426
0.0319	8.0	60000	0.4505	0.9425
0.0191	9.0	67500	0.4649	0.9399
0.013	10.0	75000	0.5064	0.9403
0.0184	11.0	82500	0.4858	0.9405
0.0081	12.0	90000	0.5358	0.9432
0.0065	13.0	97500	0.5440	0.9436
0.0053	14.0	105000	0.5755	0.9436
0.0017	15.0	112500	0.5907	0.9457
0.0042	16.0	120000	0.5916	0.9455
0.0031	17.0	127500	0.5976	0.9468
0.0017	18.0	135000	0.6063	0.9474
0.0003	19.0	142500	0.6248	0.9467
0.0003	20.0	150000	0.6408	0.9464

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3