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metadata
tags:
  - generated_from_trainer
model-index:
  - name: 1L-BERT-finetuned-newcode
    results: []

1L-BERT-finetuned-newcode

This model is a fine-tuned version of Youssef320/LSTM-finetuned-50label-15epoch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.0668
  • Top 1 Macro F1 Score: 0.1385
  • Top 1 Weighted F1score: 0.1902
  • Top 3 Macro F1 Score: 0.2868
  • Top3 3 Weighted F1 Score : 0.3758

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: 0.0002
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 2048
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Top 1 Macro F1 Score Top 1 Weighted F1score Top 3 Macro F1 Score Top3 3 Weighted F1 Score
2.8006 0.13 32 3.1069 0.1217 0.1745 0.2614 0.3568
2.8197 0.26 64 3.0678 0.1271 0.1797 0.2715 0.3654
2.7933 0.4 96 3.0518 0.1279 0.1819 0.2714 0.3661
2.7852 0.53 128 3.0463 0.1322 0.1853 0.2787 0.3699
2.7847 0.66 160 3.0273 0.1294 0.1817 0.2773 0.3725
2.7899 0.79 192 3.0185 0.1316 0.1877 0.2769 0.3717
2.793 0.93 224 3.0140 0.1332 0.1864 0.2794 0.3731
2.6818 1.06 256 3.0629 0.1345 0.1879 0.2829 0.3739
2.6676 1.19 288 3.0798 0.1335 0.1867 0.2806 0.3724
2.6859 1.32 320 3.0595 0.1320 0.1845 0.2787 0.3704
2.6939 1.45 352 3.0650 0.1321 0.1841 0.2801 0.3710
2.7114 1.59 384 3.0594 0.1319 0.1841 0.2823 0.3735
2.7414 1.72 416 3.0475 0.1340 0.1864 0.2788 0.3710
2.7102 1.85 448 3.0464 0.1347 0.1883 0.2817 0.3741
2.7537 1.98 480 3.0270 0.1344 0.1879 0.2794 0.3736
2.616 2.12 512 3.0929 0.1361 0.1883 0.2798 0.3706
2.621 2.25 544 3.0821 0.1347 0.1867 0.2785 0.3709
2.6409 2.38 576 3.0870 0.1352 0.1873 0.2806 0.3705
2.6904 2.51 608 3.0735 0.1349 0.1867 0.2854 0.3748
2.6531 2.64 640 3.0732 0.1357 0.1895 0.2820 0.3731
2.6643 2.78 672 3.0677 0.1374 0.1896 0.2814 0.3729
2.6948 2.91 704 3.0668 0.1385 0.1902 0.2868 0.3758

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.1+cu102
  • Datasets 2.0.0
  • Tokenizers 0.11.0