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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: distilbert-base-uncased_fold_2_binary
    results: []

distilbert-base-uncased_fold_2_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: 0.4724
  • F1: 0.7604

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 1.0 290 0.4280 0.7515
0.4018 2.0 580 0.4724 0.7604
0.4018 3.0 870 0.5336 0.7428
0.1995 4.0 1160 0.8367 0.7476
0.1995 5.0 1450 0.9242 0.7412
0.089 6.0 1740 1.0987 0.7410
0.0318 7.0 2030 1.1853 0.7584
0.0318 8.0 2320 1.2509 0.7500
0.0189 9.0 2610 1.5060 0.7258
0.0189 10.0 2900 1.5607 0.7534
0.0084 11.0 3190 1.5871 0.7476
0.0084 12.0 3480 1.7206 0.7338
0.0047 13.0 3770 1.6776 0.7340
0.0068 14.0 4060 1.7339 0.7546
0.0068 15.0 4350 1.8279 0.7504
0.0025 16.0 4640 1.7791 0.7411
0.0025 17.0 4930 1.7917 0.7444
0.003 18.0 5220 1.7781 0.7559
0.0029 19.0 5510 1.8153 0.7559
0.0029 20.0 5800 1.7757 0.7414
0.0055 21.0 6090 1.8635 0.7454
0.0055 22.0 6380 1.8483 0.7460
0.001 23.0 6670 1.8620 0.7492
0.001 24.0 6960 1.9058 0.7508
0.0006 25.0 7250 1.8640 0.7504

Framework versions

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