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recipe-distilbert-s

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0321

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: 256
  • eval_batch_size: 256
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.8594 1.0 844 1.4751
1.4763 2.0 1688 1.3282
1.3664 3.0 2532 1.2553
1.2975 4.0 3376 1.2093
1.2543 5.0 4220 1.1667
1.2189 6.0 5064 1.1472
1.1944 7.0 5908 1.1251
1.1737 8.0 6752 1.1018
1.1549 9.0 7596 1.0950
1.1387 10.0 8440 1.0796
1.1295 11.0 9284 1.0713
1.1166 12.0 10128 1.0639
1.1078 13.0 10972 1.0485
1.099 14.0 11816 1.0431
1.0951 15.0 12660 1.0425
1.0874 16.0 13504 1.0323
1.0828 17.0 14348 1.0368
1.0802 18.0 15192 1.0339
1.0798 19.0 16036 1.0247
1.0758 20.0 16880 1.0321

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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