Edit model card

N_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: 0.6563
  • Accuracy: 0.9432

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
0.1786 1.0 7500 0.1921 0.9395
0.1379 2.0 15000 0.1926 0.9447
0.1163 3.0 22500 0.2237 0.9443
0.0863 4.0 30000 0.2627 0.9432
0.0551 5.0 37500 0.3291 0.9412
0.0422 6.0 45000 0.3613 0.9464
0.0356 7.0 52500 0.4004 0.9405
0.0319 8.0 60000 0.4574 0.9388
0.0229 9.0 67500 0.4549 0.9404
0.0173 10.0 75000 0.4684 0.9420
0.0173 11.0 82500 0.4891 0.9405
0.0097 12.0 90000 0.5301 0.9418
0.0088 13.0 97500 0.5361 0.9409
0.0061 14.0 105000 0.5930 0.9433
0.0031 15.0 112500 0.5658 0.9438
0.0037 16.0 120000 0.6000 0.9420
0.0023 17.0 127500 0.6230 0.9420
0.0003 18.0 135000 0.6184 0.9441
0.0003 19.0 142500 0.6488 0.9426
0.0007 20.0 150000 0.6563 0.9432

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3
Downloads last month
8
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Realgon/N_distilbert_agnews_padding30model

Finetuned
(6572)
this model

Dataset used to train Realgon/N_distilbert_agnews_padding30model

Evaluation results