metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding50model
    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: 0.9432894736842106

distilbert_agnews_padding50model

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: 0.6727
Accuracy: 0.9433

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
0.1828	1.0	7500	0.1902	0.94
0.1398	2.0	15000	0.1989	0.9433
0.1177	3.0	22500	0.2083	0.9459
0.0933	4.0	30000	0.2547	0.9439
0.0648	5.0	37500	0.3024	0.9428
0.0427	6.0	45000	0.3627	0.9401
0.034	7.0	52500	0.4282	0.9362
0.0325	8.0	60000	0.4297	0.9404
0.0217	9.0	67500	0.4508	0.9387
0.0126	10.0	75000	0.4900	0.9397
0.0147	11.0	82500	0.5530	0.9399
0.0103	12.0	90000	0.5293	0.9408
0.0108	13.0	97500	0.5388	0.9413
0.0068	14.0	105000	0.6006	0.9397
0.0028	15.0	112500	0.5974	0.9432
0.005	16.0	120000	0.5617	0.9413
0.0027	17.0	127500	0.6217	0.9433
0.0004	18.0	135000	0.6415	0.9420
0.0011	19.0	142500	0.6566	0.9442
0.0004	20.0	150000	0.6727	0.9433

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3