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recipe-distilbert-upper-Is

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: 0.8565

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
1.6309 1.0 1305 1.2607
1.2639 2.0 2610 1.1291
1.1592 3.0 3915 1.0605
1.0987 4.0 5220 1.0128
1.0569 5.0 6525 0.9796
1.0262 6.0 7830 0.9592
1.0032 7.0 9135 0.9352
0.9815 8.0 10440 0.9186
0.967 9.0 11745 0.9086
0.9532 10.0 13050 0.8973
0.9436 11.0 14355 0.8888
0.9318 12.0 15660 0.8835
0.9243 13.0 16965 0.8748
0.9169 14.0 18270 0.8673
0.9117 15.0 19575 0.8610
0.9066 16.0 20880 0.8562
0.9028 17.0 22185 0.8566
0.901 18.0 23490 0.8583
0.8988 19.0 24795 0.8557
0.8958 20.0 26100 0.8565

Framework versions

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