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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: distilbert-base-uncased_fold_1_binary
    results: []

distilbert-base-uncased_fold_1_binary

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: 1.1222
  • F1: 0.7596

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: 25

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 288 0.4130 0.7517
0.3938 2.0 576 0.4260 0.7330
0.3938 3.0 864 0.5000 0.7488
0.19 4.0 1152 0.7415 0.7487
0.19 5.0 1440 0.8994 0.7397
0.0903 6.0 1728 0.9835 0.7386
0.0392 7.0 2016 1.1222 0.7596
0.0392 8.0 2304 1.2018 0.7314
0.0234 9.0 2592 1.2691 0.7330
0.0234 10.0 2880 1.2972 0.7496
0.0182 11.0 3168 1.4606 0.7492
0.0182 12.0 3456 1.4766 0.7361
0.006 13.0 3744 1.4888 0.7500
0.0057 14.0 4032 1.5684 0.7298
0.0057 15.0 4320 1.5354 0.7509
0.0058 16.0 4608 1.7733 0.7436
0.0058 17.0 4896 1.5695 0.7512
0.0089 18.0 5184 1.6593 0.7430
0.0089 19.0 5472 1.7092 0.7444
0.0048 20.0 5760 1.7206 0.7374
0.002 21.0 6048 1.7440 0.7343
0.002 22.0 6336 1.7582 0.7347
0.0006 23.0 6624 1.7294 0.7472
0.0006 24.0 6912 1.7454 0.7365
0.0001 25.0 7200 1.7395 0.7429

Framework versions

  • Transformers 4.21.0
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1