--- license: apache-2.0 tags: - generated_from_trainer datasets: - super_glue metrics: - accuracy model-index: - name: '20230822202110' results: [] --- # 20230822202110 This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset. It achieves the following results on the evaluation set: - Loss: 0.1679 - Accuracy: 0.7148 ## 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: 0.003 - train_batch_size: 16 - eval_batch_size: 8 - seed: 11 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 60.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 156 | 0.4220 | 0.5271 | | No log | 2.0 | 312 | 0.2767 | 0.4729 | | No log | 3.0 | 468 | 0.4345 | 0.4729 | | 0.2507 | 4.0 | 624 | 0.2006 | 0.5343 | | 0.2507 | 5.0 | 780 | 0.1797 | 0.4729 | | 0.2507 | 6.0 | 936 | 0.2180 | 0.5271 | | 0.2023 | 7.0 | 1092 | 0.1726 | 0.5054 | | 0.2023 | 8.0 | 1248 | 0.1811 | 0.4729 | | 0.2023 | 9.0 | 1404 | 0.1828 | 0.5451 | | 0.2077 | 10.0 | 1560 | 0.1921 | 0.5343 | | 0.2077 | 11.0 | 1716 | 0.1772 | 0.4838 | | 0.2077 | 12.0 | 1872 | 0.1724 | 0.6462 | | 0.189 | 13.0 | 2028 | 0.1718 | 0.5379 | | 0.189 | 14.0 | 2184 | 0.1728 | 0.5126 | | 0.189 | 15.0 | 2340 | 0.1775 | 0.5126 | | 0.189 | 16.0 | 2496 | 0.1813 | 0.5596 | | 0.1803 | 17.0 | 2652 | 0.1739 | 0.6318 | | 0.1803 | 18.0 | 2808 | 0.1718 | 0.6137 | | 0.1803 | 19.0 | 2964 | 0.1711 | 0.6390 | | 0.1791 | 20.0 | 3120 | 0.1797 | 0.5957 | | 0.1791 | 21.0 | 3276 | 0.1710 | 0.6859 | | 0.1791 | 22.0 | 3432 | 0.1729 | 0.6643 | | 0.1781 | 23.0 | 3588 | 0.1701 | 0.6823 | | 0.1781 | 24.0 | 3744 | 0.1706 | 0.6390 | | 0.1781 | 25.0 | 3900 | 0.1708 | 0.6859 | | 0.1765 | 26.0 | 4056 | 0.1697 | 0.6643 | | 0.1765 | 27.0 | 4212 | 0.1698 | 0.6715 | | 0.1765 | 28.0 | 4368 | 0.1710 | 0.6426 | | 0.176 | 29.0 | 4524 | 0.1710 | 0.6931 | | 0.176 | 30.0 | 4680 | 0.1703 | 0.6968 | | 0.176 | 31.0 | 4836 | 0.1725 | 0.6570 | | 0.176 | 32.0 | 4992 | 0.1699 | 0.6715 | | 0.1749 | 33.0 | 5148 | 0.1710 | 0.6895 | | 0.1749 | 34.0 | 5304 | 0.1694 | 0.7220 | | 0.1749 | 35.0 | 5460 | 0.1700 | 0.6534 | | 0.1739 | 36.0 | 5616 | 0.1690 | 0.7112 | | 0.1739 | 37.0 | 5772 | 0.1685 | 0.7220 | | 0.1739 | 38.0 | 5928 | 0.1696 | 0.7040 | | 0.1738 | 39.0 | 6084 | 0.1688 | 0.7148 | | 0.1738 | 40.0 | 6240 | 0.1692 | 0.7220 | | 0.1738 | 41.0 | 6396 | 0.1683 | 0.7365 | | 0.1726 | 42.0 | 6552 | 0.1690 | 0.6679 | | 0.1726 | 43.0 | 6708 | 0.1679 | 0.7076 | | 0.1726 | 44.0 | 6864 | 0.1691 | 0.7184 | | 0.1719 | 45.0 | 7020 | 0.1692 | 0.7292 | | 0.1719 | 46.0 | 7176 | 0.1685 | 0.7329 | | 0.1719 | 47.0 | 7332 | 0.1684 | 0.7184 | | 0.1719 | 48.0 | 7488 | 0.1690 | 0.7112 | | 0.1712 | 49.0 | 7644 | 0.1690 | 0.7292 | | 0.1712 | 50.0 | 7800 | 0.1685 | 0.6931 | | 0.1712 | 51.0 | 7956 | 0.1680 | 0.7256 | | 0.1705 | 52.0 | 8112 | 0.1687 | 0.7076 | | 0.1705 | 53.0 | 8268 | 0.1685 | 0.7184 | | 0.1705 | 54.0 | 8424 | 0.1689 | 0.7365 | | 0.1705 | 55.0 | 8580 | 0.1677 | 0.7148 | | 0.1705 | 56.0 | 8736 | 0.1694 | 0.7220 | | 0.1705 | 57.0 | 8892 | 0.1682 | 0.7256 | | 0.1692 | 58.0 | 9048 | 0.1684 | 0.7148 | | 0.1692 | 59.0 | 9204 | 0.1679 | 0.7148 | | 0.1692 | 60.0 | 9360 | 0.1679 | 0.7148 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3