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distilbert-base-uncased-finetuned-pfe

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9517

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: 32
  • eval_batch_size: 32
  • 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
No log 1.0 6 2.8673
No log 2.0 12 2.7271
No log 3.0 18 2.5814
No log 4.0 24 2.5083
No log 5.0 30 2.3478
No log 6.0 36 2.3432
No log 7.0 42 2.2518
No log 8.0 48 2.2160
No log 9.0 54 2.1958
No log 10.0 60 2.1662
No log 11.0 66 2.1043
No log 12.0 72 2.0557
No log 13.0 78 2.0443
No log 14.0 84 1.9886
No log 15.0 90 1.9999
No log 16.0 96 1.9629
No log 17.0 102 1.9503
No log 18.0 108 1.9439
No log 19.0 114 1.9504
No log 20.0 120 1.9517

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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66.4M params
Tensor type
F32

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