metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: distilbert_agnews_padding30model
    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: 0.9426315789473684

distilbert_agnews_padding30model

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: 0.6664
Accuracy: 0.9426

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
0.1798	1.0	7500	0.1996	0.9397
0.1377	2.0	15000	0.1984	0.9432
0.1168	3.0	22500	0.2269	0.9429
0.0831	4.0	30000	0.2763	0.9411
0.0581	5.0	37500	0.2916	0.9428
0.0422	6.0	45000	0.3627	0.9424
0.0296	7.0	52500	0.4506	0.94
0.0315	8.0	60000	0.4401	0.9417
0.0224	9.0	67500	0.4668	0.9426
0.0151	10.0	75000	0.5095	0.9416
0.0202	11.0	82500	0.5013	0.9437
0.009	12.0	90000	0.5612	0.9441
0.0105	13.0	97500	0.5372	0.9432
0.0105	14.0	105000	0.5760	0.9409
0.0044	15.0	112500	0.5765	0.9417
0.0029	16.0	120000	0.6285	0.9432
0.002	17.0	127500	0.6484	0.9416
0.0006	18.0	135000	0.6568	0.9428
0.0002	19.0	142500	0.6537	0.9437
0.0004	20.0	150000	0.6664	0.9426

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3