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update model card README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - crows_pairs
metrics:
  - accuracy
model-index:
  - name: t5-small_crows_pairs_finetuned
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: crows_pairs
          type: crows_pairs
          config: crows_pairs
          split: test
          args: crows_pairs
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7218543046357616

t5-small_crows_pairs_finetuned

This model is a fine-tuned version of t5-small on the crows_pairs dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0876
  • Accuracy: 0.7219
  • Tp: 0.4901
  • Tn: 0.2318
  • Fp: 0.2649
  • Fn: 0.0132

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: 0.0005
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy Tp Tn Fp Fn
0.4776 0.53 20 0.3559 0.5033 0.5033 0.0 0.4967 0.0
0.3708 1.05 40 0.3431 0.5265 0.5033 0.0232 0.4735 0.0
0.3905 1.58 60 0.3414 0.6325 0.5033 0.1291 0.3675 0.0
0.3526 2.11 80 0.3260 0.5464 0.5033 0.0430 0.4536 0.0
0.2734 2.63 100 0.3047 0.8179 0.4934 0.3245 0.1722 0.0099
0.2429 3.16 120 0.2631 0.6623 0.5033 0.1589 0.3377 0.0
0.2161 3.68 140 0.2829 0.7152 0.4901 0.2252 0.2715 0.0132
0.1617 4.21 160 0.2947 0.7748 0.4901 0.2848 0.2119 0.0132
0.1776 4.74 180 0.3258 0.7384 0.4901 0.2483 0.2483 0.0132
0.1113 5.26 200 0.3362 0.7815 0.4901 0.2914 0.2053 0.0132
0.1008 5.79 220 0.4016 0.7748 0.4868 0.2881 0.2086 0.0166
0.0572 6.32 240 0.4486 0.7219 0.4901 0.2318 0.2649 0.0132
0.0701 6.84 260 0.4561 0.7384 0.4901 0.2483 0.2483 0.0132
0.051 7.37 280 0.4813 0.7815 0.4868 0.2947 0.2020 0.0166
0.0408 7.89 300 0.5279 0.7815 0.4868 0.2947 0.2020 0.0166
0.0326 8.42 320 0.6454 0.7550 0.4934 0.2616 0.2351 0.0099
0.0361 8.95 340 0.7559 0.7417 0.4901 0.2517 0.2450 0.0132
0.0304 9.47 360 0.7422 0.7318 0.4868 0.2450 0.2517 0.0166
0.0299 10.0 380 0.7770 0.7450 0.4868 0.2583 0.2384 0.0166
0.0227 10.53 400 0.7033 0.7947 0.4801 0.3146 0.1821 0.0232
0.017 11.05 420 0.7220 0.7649 0.4801 0.2848 0.2119 0.0232
0.0166 11.58 440 0.7674 0.7649 0.4636 0.3013 0.1954 0.0397
0.0123 12.11 460 0.8153 0.7616 0.4834 0.2781 0.2185 0.0199
0.0084 12.63 480 0.8422 0.7483 0.4834 0.2649 0.2318 0.0199
0.0178 13.16 500 0.7960 0.7649 0.4735 0.2914 0.2053 0.0298
0.016 13.68 520 0.8152 0.7086 0.4834 0.2252 0.2715 0.0199
0.007 14.21 540 0.8518 0.6589 0.4901 0.1689 0.3278 0.0132
0.0019 14.74 560 0.8647 0.7020 0.4834 0.2185 0.2781 0.0199
0.0159 15.26 580 0.8817 0.7086 0.4834 0.2252 0.2715 0.0199
0.0016 15.79 600 0.9105 0.6689 0.4834 0.1854 0.3113 0.0199
0.0079 16.32 620 0.9311 0.7053 0.4834 0.2219 0.2748 0.0199
0.0045 16.84 640 0.9586 0.7086 0.4834 0.2252 0.2715 0.0199
0.0033 17.37 660 0.9765 0.7252 0.4834 0.2417 0.2550 0.0199
0.0078 17.89 680 1.0263 0.7086 0.4834 0.2252 0.2715 0.0199
0.0047 18.42 700 0.9929 0.7351 0.4768 0.2583 0.2384 0.0265
0.0082 18.95 720 1.0001 0.7185 0.4801 0.2384 0.2583 0.0232
0.0022 19.47 740 1.0150 0.7086 0.4801 0.2285 0.2682 0.0232
0.0027 20.0 760 1.0638 0.6887 0.4901 0.1987 0.2980 0.0132
0.0025 20.53 780 1.0124 0.7020 0.4834 0.2185 0.2781 0.0199
0.007 21.05 800 1.0082 0.6987 0.4834 0.2152 0.2815 0.0199
0.0119 21.58 820 1.0225 0.7119 0.4801 0.2318 0.2649 0.0232
0.0016 22.11 840 1.0494 0.7053 0.4901 0.2152 0.2815 0.0132
0.0007 22.63 860 1.0515 0.7152 0.4868 0.2285 0.2682 0.0166
0.0014 23.16 880 1.0492 0.7119 0.4868 0.2252 0.2715 0.0166
0.002 23.68 900 1.0970 0.7020 0.4934 0.2086 0.2881 0.0099
0.0003 24.21 920 1.0429 0.7185 0.4834 0.2351 0.2616 0.0199
0.0002 24.74 940 1.0772 0.7053 0.4868 0.2185 0.2781 0.0166
0.0008 25.26 960 1.0766 0.7119 0.4934 0.2185 0.2781 0.0099
0.001 25.79 980 1.0720 0.7185 0.4934 0.2252 0.2715 0.0099
0.0002 26.32 1000 1.0763 0.7152 0.4901 0.2252 0.2715 0.0132
0.0002 26.84 1020 1.0675 0.7185 0.4901 0.2285 0.2682 0.0132
0.0011 27.37 1040 1.0745 0.7185 0.4834 0.2351 0.2616 0.0199
0.0007 27.89 1060 1.0792 0.7185 0.4901 0.2285 0.2682 0.0132
0.0007 28.42 1080 1.0880 0.7152 0.4934 0.2219 0.2748 0.0099
0.0005 28.95 1100 1.0903 0.7185 0.4934 0.2252 0.2715 0.0099
0.0025 29.47 1120 1.0877 0.7185 0.4901 0.2285 0.2682 0.0132
0.0004 30.0 1140 1.0876 0.7219 0.4901 0.2318 0.2649 0.0132

Framework versions

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