metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding10model
    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: 0.9444736842105264

distilbert_agnews_padding10model

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: 0.6613
Accuracy: 0.9445

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
0.1788	1.0	7500	0.1962	0.9405
0.1396	2.0	15000	0.1946	0.9446
0.1159	3.0	22500	0.2336	0.9433
0.0802	4.0	30000	0.2599	0.9437
0.055	5.0	37500	0.3196	0.9432
0.0408	6.0	45000	0.4017	0.9434
0.0338	7.0	52500	0.4113	0.9412
0.0258	8.0	60000	0.4533	0.9416
0.0159	9.0	67500	0.4573	0.9442
0.0154	10.0	75000	0.4980	0.9420
0.0171	11.0	82500	0.4935	0.9420
0.0105	12.0	90000	0.5304	0.9399
0.0079	13.0	97500	0.5437	0.9439
0.0061	14.0	105000	0.5889	0.9429
0.0056	15.0	112500	0.5444	0.9426
0.0059	16.0	120000	0.6274	0.9429
0.0004	17.0	127500	0.6264	0.9428
0.0014	18.0	135000	0.6138	0.9441
0.0002	19.0	142500	0.6431	0.9447
0.0005	20.0	150000	0.6613	0.9445

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3