nb-bert-base_FGN / README.md
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metadata
license: cc-by-4.0
base_model: NbAiLab/nb-bert-base
tags:
  - generated_from_trainer
model-index:
  - name: nb-bert-base_FGN
    results: []

nb-bert-base_FGN

This model is a fine-tuned version of NbAiLab/nb-bert-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0904
  • F1-score: 0.8074

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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 F1-score
No log 1.0 120 0.6228 0.7307
No log 2.0 240 0.7442 0.7474
No log 3.0 360 0.7118 0.7785
No log 4.0 480 1.2081 0.7137
0.5388 5.0 600 1.1968 0.7628
0.5388 6.0 720 1.0904 0.8074
0.5388 7.0 840 1.2685 0.8007
0.5388 8.0 960 1.4070 0.7783
0.123 9.0 1080 1.6120 0.7608
0.123 10.0 1200 1.5899 0.7695
0.123 11.0 1320 1.4975 0.7705
0.123 12.0 1440 1.4624 0.7983
0.0475 13.0 1560 1.5148 0.7711
0.0475 14.0 1680 1.4680 0.7926
0.0475 15.0 1800 1.4216 0.8006
0.0475 16.0 1920 1.4962 0.8006
0.0201 17.0 2040 1.4150 0.7883
0.0201 18.0 2160 1.4259 0.7755
0.0201 19.0 2280 1.5040 0.7799
0.0201 20.0 2400 1.5045 0.7808

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1