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N_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: 0.6711
  • Accuracy: 0.9438

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
0.1775 1.0 7500 0.1897 0.9399
0.1357 2.0 15000 0.1881 0.9464
0.1124 3.0 22500 0.2236 0.9453
0.0822 4.0 30000 0.2775 0.9439
0.0517 5.0 37500 0.3485 0.9370
0.0405 6.0 45000 0.3514 0.9418
0.0356 7.0 52500 0.4108 0.9409
0.0292 8.0 60000 0.4351 0.9411
0.0191 9.0 67500 0.4604 0.9374
0.0159 10.0 75000 0.4604 0.9429
0.0126 11.0 82500 0.4860 0.9409
0.0092 12.0 90000 0.5452 0.9416
0.0075 13.0 97500 0.5498 0.9442
0.0023 14.0 105000 0.5712 0.9417
0.0015 15.0 112500 0.6107 0.9420
0.0033 16.0 120000 0.5908 0.9428
0.0029 17.0 127500 0.6449 0.9416
0.0009 18.0 135000 0.6534 0.9430
0.0013 19.0 142500 0.6641 0.9442
0.0005 20.0 150000 0.6711 0.9438

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Safetensors
Model size
67M params
Tensor type
F32
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Finetuned from

Dataset used to train Realgon/N_distilbert_agnews_padding10model

Evaluation results