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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased_fold_1_ternary
    results: []

distilbert-base-uncased_fold_1_ternary

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: 2.0582
  • F1: 0.7326

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 0.5524 0.6755
0.5648 2.0 580 0.5654 0.7124
0.5648 3.0 870 0.6547 0.6896
0.2712 4.0 1160 0.8916 0.7263
0.2712 5.0 1450 1.1187 0.7120
0.1147 6.0 1740 1.2778 0.7114
0.0476 7.0 2030 1.4441 0.7151
0.0476 8.0 2320 1.5535 0.7133
0.0187 9.0 2610 1.6439 0.7212
0.0187 10.0 2900 1.7261 0.7313
0.0138 11.0 3190 1.6806 0.7292
0.0138 12.0 3480 1.8425 0.7111
0.009 13.0 3770 1.9207 0.7213
0.0045 14.0 4060 1.8900 0.7202
0.0045 15.0 4350 1.9730 0.7216
0.0042 16.0 4640 2.0775 0.7041
0.0042 17.0 4930 2.0514 0.7106
0.0019 18.0 5220 2.0582 0.7326
0.0039 19.0 5510 2.1010 0.7081
0.0039 20.0 5800 2.0487 0.7273
0.0025 21.0 6090 2.0415 0.7254
0.0025 22.0 6380 2.0753 0.7157
0.0017 23.0 6670 2.0554 0.7246
0.0017 24.0 6960 2.0644 0.7290
0.0001 25.0 7250 2.0711 0.7310

Framework versions

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