--- license: apache-2.0 tags: - generated_from_trainer datasets: - super_glue metrics: - accuracy model-index: - name: '20230826081833' results: [] --- # 20230826081833 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: 0.6393 - Accuracy: 0.69 ## 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: 0.05 - 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: 80.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 25 | 0.7348 | 0.6 | | No log | 2.0 | 50 | 0.6045 | 0.61 | | No log | 3.0 | 75 | 0.9239 | 0.62 | | No log | 4.0 | 100 | 0.6379 | 0.69 | | No log | 5.0 | 125 | 0.5724 | 0.72 | | No log | 6.0 | 150 | 1.2083 | 0.69 | | No log | 7.0 | 175 | 1.3074 | 0.67 | | No log | 8.0 | 200 | 1.1626 | 0.7 | | No log | 9.0 | 225 | 1.0019 | 0.64 | | No log | 10.0 | 250 | 0.6240 | 0.73 | | No log | 11.0 | 275 | 1.0829 | 0.66 | | No log | 12.0 | 300 | 0.8053 | 0.66 | | No log | 13.0 | 325 | 1.1526 | 0.63 | | No log | 14.0 | 350 | 1.2006 | 0.69 | | No log | 15.0 | 375 | 1.1382 | 0.67 | | No log | 16.0 | 400 | 1.1345 | 0.71 | | No log | 17.0 | 425 | 1.5029 | 0.67 | | No log | 18.0 | 450 | 1.3780 | 0.67 | | No log | 19.0 | 475 | 1.1811 | 0.66 | | 1.3151 | 20.0 | 500 | 1.2461 | 0.7 | | 1.3151 | 21.0 | 525 | 1.2269 | 0.68 | | 1.3151 | 22.0 | 550 | 1.1515 | 0.68 | | 1.3151 | 23.0 | 575 | 0.9944 | 0.66 | | 1.3151 | 24.0 | 600 | 1.2708 | 0.67 | | 1.3151 | 25.0 | 625 | 1.5817 | 0.65 | | 1.3151 | 26.0 | 650 | 1.0934 | 0.71 | | 1.3151 | 27.0 | 675 | 1.4179 | 0.67 | | 1.3151 | 28.0 | 700 | 1.4260 | 0.65 | | 1.3151 | 29.0 | 725 | 1.3818 | 0.65 | | 1.3151 | 30.0 | 750 | 1.7166 | 0.66 | | 1.3151 | 31.0 | 775 | 1.1710 | 0.64 | | 1.3151 | 32.0 | 800 | 1.0660 | 0.64 | | 1.3151 | 33.0 | 825 | 1.0127 | 0.69 | | 1.3151 | 34.0 | 850 | 0.9810 | 0.68 | | 1.3151 | 35.0 | 875 | 1.1077 | 0.7 | | 1.3151 | 36.0 | 900 | 1.0629 | 0.66 | | 1.3151 | 37.0 | 925 | 1.5933 | 0.69 | | 1.3151 | 38.0 | 950 | 1.1322 | 0.71 | | 1.3151 | 39.0 | 975 | 1.0735 | 0.73 | | 0.6791 | 40.0 | 1000 | 0.8940 | 0.72 | | 0.6791 | 41.0 | 1025 | 0.9349 | 0.67 | | 0.6791 | 42.0 | 1050 | 0.8962 | 0.67 | | 0.6791 | 43.0 | 1075 | 1.0663 | 0.69 | | 0.6791 | 44.0 | 1100 | 0.9681 | 0.69 | | 0.6791 | 45.0 | 1125 | 0.7694 | 0.68 | | 0.6791 | 46.0 | 1150 | 1.0311 | 0.71 | | 0.6791 | 47.0 | 1175 | 0.7407 | 0.7 | | 0.6791 | 48.0 | 1200 | 0.6861 | 0.69 | | 0.6791 | 49.0 | 1225 | 0.9920 | 0.69 | | 0.6791 | 50.0 | 1250 | 0.7187 | 0.69 | | 0.6791 | 51.0 | 1275 | 0.7602 | 0.72 | | 0.6791 | 52.0 | 1300 | 0.7285 | 0.69 | | 0.6791 | 53.0 | 1325 | 0.8233 | 0.68 | | 0.6791 | 54.0 | 1350 | 0.7932 | 0.7 | | 0.6791 | 55.0 | 1375 | 0.8861 | 0.71 | | 0.6791 | 56.0 | 1400 | 0.7877 | 0.71 | | 0.6791 | 57.0 | 1425 | 0.7689 | 0.7 | | 0.6791 | 58.0 | 1450 | 0.7919 | 0.7 | | 0.6791 | 59.0 | 1475 | 0.7441 | 0.7 | | 0.3594 | 60.0 | 1500 | 0.8327 | 0.69 | | 0.3594 | 61.0 | 1525 | 0.6414 | 0.71 | | 0.3594 | 62.0 | 1550 | 0.6702 | 0.71 | | 0.3594 | 63.0 | 1575 | 0.6862 | 0.71 | | 0.3594 | 64.0 | 1600 | 0.6349 | 0.68 | | 0.3594 | 65.0 | 1625 | 0.6800 | 0.69 | | 0.3594 | 66.0 | 1650 | 0.7005 | 0.69 | | 0.3594 | 67.0 | 1675 | 0.7058 | 0.71 | | 0.3594 | 68.0 | 1700 | 0.6880 | 0.73 | | 0.3594 | 69.0 | 1725 | 0.6774 | 0.72 | | 0.3594 | 70.0 | 1750 | 0.6816 | 0.73 | | 0.3594 | 71.0 | 1775 | 0.7138 | 0.72 | | 0.3594 | 72.0 | 1800 | 0.6311 | 0.69 | | 0.3594 | 73.0 | 1825 | 0.6579 | 0.69 | | 0.3594 | 74.0 | 1850 | 0.6956 | 0.69 | | 0.3594 | 75.0 | 1875 | 0.6341 | 0.69 | | 0.3594 | 76.0 | 1900 | 0.6722 | 0.7 | | 0.3594 | 77.0 | 1925 | 0.6459 | 0.7 | | 0.3594 | 78.0 | 1950 | 0.6351 | 0.68 | | 0.3594 | 79.0 | 1975 | 0.6436 | 0.68 | | 0.2323 | 80.0 | 2000 | 0.6393 | 0.69 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3