asun17904's picture
update model card README.md
2a1b41e
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - crows_pairs
metrics:
  - accuracy
model-index:
  - name: multiberts-seed_1_crows_pairs_classifieronly
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: crows_pairs
          type: crows_pairs
          config: crows_pairs
          split: test
          args: crows_pairs
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5331125827814569

multiberts-seed_1_crows_pairs_classifieronly

This model is a fine-tuned version of google/multiberts-seed_1 on the crows_pairs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6903
  • Accuracy: 0.5331
  • Tp: 0.3477
  • Tn: 0.1854
  • Fp: 0.3146
  • Fn: 0.1523

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy Tp Tn Fp Fn
0.7016 1.05 20 0.6910 0.5364 0.4437 0.0927 0.4073 0.0563
0.7072 2.11 40 0.6914 0.5166 0.4834 0.0331 0.4669 0.0166
0.7003 3.16 60 0.6910 0.5497 0.0927 0.4570 0.0430 0.4073
0.7004 4.21 80 0.6908 0.5265 0.2583 0.2682 0.2318 0.2417
0.6985 5.26 100 0.6916 0.5033 0.0033 0.5 0.0 0.4967
0.7107 6.32 120 0.6909 0.5364 0.4603 0.0762 0.4238 0.0397
0.7135 7.37 140 0.6908 0.5364 0.4139 0.1225 0.3775 0.0861
0.7041 8.42 160 0.6908 0.5464 0.2848 0.2616 0.2384 0.2152
0.7022 9.47 180 0.6907 0.5298 0.2450 0.2848 0.2152 0.2550
0.6996 10.53 200 0.6908 0.5265 0.4371 0.0894 0.4106 0.0629
0.7049 11.58 220 0.6914 0.5066 0.0066 0.5 0.0 0.4934
0.6975 12.63 240 0.6912 0.5232 0.4834 0.0397 0.4603 0.0166
0.6967 13.68 260 0.6907 0.5497 0.2748 0.2748 0.2252 0.2252
0.705 14.74 280 0.6912 0.5132 0.0132 0.5 0.0 0.4868
0.6943 15.79 300 0.6909 0.5298 0.4768 0.0530 0.4470 0.0232
0.7057 16.84 320 0.6906 0.5364 0.4272 0.1093 0.3907 0.0728
0.6995 17.89 340 0.6905 0.5530 0.2252 0.3278 0.1722 0.2748
0.6989 18.95 360 0.6905 0.5464 0.1854 0.3609 0.1391 0.3146
0.7156 20.0 380 0.6912 0.5199 0.4834 0.0364 0.4636 0.0166
0.6957 21.05 400 0.6905 0.5497 0.2285 0.3212 0.1788 0.2715
0.6978 22.11 420 0.6906 0.5331 0.4371 0.0960 0.4040 0.0629
0.6988 23.16 440 0.6905 0.5331 0.3179 0.2152 0.2848 0.1821
0.7054 24.21 460 0.6905 0.5497 0.1623 0.3874 0.1126 0.3377
0.6997 25.26 480 0.6907 0.5166 0.4636 0.0530 0.4470 0.0364
0.7007 26.32 500 0.6904 0.5364 0.3940 0.1424 0.3576 0.1060
0.6973 27.37 520 0.6914 0.5 0.0 0.5 0.0 0.5
0.704 28.42 540 0.6905 0.5364 0.4338 0.1026 0.3974 0.0662
0.7028 29.47 560 0.6905 0.5530 0.1192 0.4338 0.0662 0.3808
0.6959 30.53 580 0.6905 0.5364 0.4404 0.0960 0.4040 0.0596
0.704 31.58 600 0.6904 0.5464 0.2583 0.2881 0.2119 0.2417
0.704 32.63 620 0.6903 0.5397 0.3146 0.2252 0.2748 0.1854
0.7003 33.68 640 0.6903 0.5430 0.3079 0.2351 0.2649 0.1921
0.7058 34.74 660 0.6903 0.5464 0.3079 0.2384 0.2616 0.1921
0.7095 35.79 680 0.6903 0.5430 0.2649 0.2781 0.2219 0.2351
0.7019 36.84 700 0.6905 0.5397 0.0695 0.4702 0.0298 0.4305
0.7167 37.89 720 0.6907 0.5099 0.0166 0.4934 0.0066 0.4834
0.6975 38.95 740 0.6903 0.5497 0.3113 0.2384 0.2616 0.1887
0.7036 40.0 760 0.6903 0.5397 0.3311 0.2086 0.2914 0.1689
0.7009 41.05 780 0.6903 0.5331 0.3940 0.1391 0.3609 0.1060
0.7004 42.11 800 0.6903 0.5430 0.2980 0.2450 0.2550 0.2020
0.699 43.16 820 0.6903 0.5430 0.2152 0.3278 0.1722 0.2848
0.6962 44.21 840 0.6903 0.5430 0.2980 0.2450 0.2550 0.2020
0.6981 45.26 860 0.6903 0.5397 0.3543 0.1854 0.3146 0.1457
0.7008 46.32 880 0.6903 0.5430 0.3808 0.1623 0.3377 0.1192
0.7048 47.37 900 0.6903 0.5530 0.3742 0.1788 0.3212 0.1258
0.707 48.42 920 0.6903 0.5497 0.3709 0.1788 0.3212 0.1291
0.7014 49.47 940 0.6903 0.5331 0.3477 0.1854 0.3146 0.1523

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1
  • Datasets 2.10.1
  • Tokenizers 0.13.2