--- license: apache-2.0 tags: - generated_from_trainer datasets: - super_glue metrics: - accuracy model-index: - name: '20230826040158' results: [] --- # 20230826040158 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: 0.5369 - Accuracy: 0.72 ## 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: 0.01 - 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 | 0.6901 | 0.36 | | No log | 2.0 | 50 | 0.7172 | 0.56 | | No log | 3.0 | 75 | 0.6264 | 0.58 | | No log | 4.0 | 100 | 0.5864 | 0.61 | | No log | 5.0 | 125 | 0.5717 | 0.47 | | No log | 6.0 | 150 | 0.6748 | 0.4 | | No log | 7.0 | 175 | 0.5272 | 0.66 | | No log | 8.0 | 200 | 0.5651 | 0.64 | | No log | 9.0 | 225 | 0.5785 | 0.65 | | No log | 10.0 | 250 | 0.5773 | 0.65 | | No log | 11.0 | 275 | 0.5287 | 0.65 | | No log | 12.0 | 300 | 0.5612 | 0.64 | | No log | 13.0 | 325 | 0.5734 | 0.66 | | No log | 14.0 | 350 | 0.5196 | 0.65 | | No log | 15.0 | 375 | 0.5491 | 0.66 | | No log | 16.0 | 400 | 0.5137 | 0.63 | | No log | 17.0 | 425 | 0.5333 | 0.67 | | No log | 18.0 | 450 | 0.5518 | 0.66 | | No log | 19.0 | 475 | 0.5222 | 0.66 | | 0.7077 | 20.0 | 500 | 0.4976 | 0.67 | | 0.7077 | 21.0 | 525 | 0.4995 | 0.67 | | 0.7077 | 22.0 | 550 | 0.5837 | 0.65 | | 0.7077 | 23.0 | 575 | 0.5801 | 0.62 | | 0.7077 | 24.0 | 600 | 0.5377 | 0.63 | | 0.7077 | 25.0 | 625 | 0.5509 | 0.63 | | 0.7077 | 26.0 | 650 | 0.5863 | 0.67 | | 0.7077 | 27.0 | 675 | 0.5980 | 0.65 | | 0.7077 | 28.0 | 700 | 0.6482 | 0.67 | | 0.7077 | 29.0 | 725 | 0.5851 | 0.66 | | 0.7077 | 30.0 | 750 | 0.6651 | 0.67 | | 0.7077 | 31.0 | 775 | 0.5497 | 0.69 | | 0.7077 | 32.0 | 800 | 0.5907 | 0.72 | | 0.7077 | 33.0 | 825 | 0.5805 | 0.68 | | 0.7077 | 34.0 | 850 | 0.5844 | 0.69 | | 0.7077 | 35.0 | 875 | 0.5750 | 0.69 | | 0.7077 | 36.0 | 900 | 0.6175 | 0.7 | | 0.7077 | 37.0 | 925 | 0.5754 | 0.68 | | 0.7077 | 38.0 | 950 | 0.5758 | 0.69 | | 0.7077 | 39.0 | 975 | 0.6013 | 0.69 | | 0.4491 | 40.0 | 1000 | 0.5384 | 0.68 | | 0.4491 | 41.0 | 1025 | 0.5931 | 0.7 | | 0.4491 | 42.0 | 1050 | 0.6030 | 0.7 | | 0.4491 | 43.0 | 1075 | 0.5630 | 0.67 | | 0.4491 | 44.0 | 1100 | 0.5599 | 0.67 | | 0.4491 | 45.0 | 1125 | 0.5799 | 0.66 | | 0.4491 | 46.0 | 1150 | 0.5545 | 0.69 | | 0.4491 | 47.0 | 1175 | 0.5643 | 0.68 | | 0.4491 | 48.0 | 1200 | 0.5845 | 0.7 | | 0.4491 | 49.0 | 1225 | 0.5781 | 0.69 | | 0.4491 | 50.0 | 1250 | 0.5623 | 0.7 | | 0.4491 | 51.0 | 1275 | 0.5528 | 0.69 | | 0.4491 | 52.0 | 1300 | 0.5442 | 0.71 | | 0.4491 | 53.0 | 1325 | 0.5498 | 0.69 | | 0.4491 | 54.0 | 1350 | 0.5391 | 0.7 | | 0.4491 | 55.0 | 1375 | 0.5570 | 0.71 | | 0.4491 | 56.0 | 1400 | 0.5729 | 0.71 | | 0.4491 | 57.0 | 1425 | 0.5352 | 0.72 | | 0.4491 | 58.0 | 1450 | 0.5538 | 0.7 | | 0.4491 | 59.0 | 1475 | 0.5563 | 0.71 | | 0.3353 | 60.0 | 1500 | 0.5704 | 0.71 | | 0.3353 | 61.0 | 1525 | 0.5726 | 0.7 | | 0.3353 | 62.0 | 1550 | 0.5694 | 0.7 | | 0.3353 | 63.0 | 1575 | 0.5714 | 0.71 | | 0.3353 | 64.0 | 1600 | 0.5551 | 0.7 | | 0.3353 | 65.0 | 1625 | 0.5548 | 0.7 | | 0.3353 | 66.0 | 1650 | 0.5430 | 0.7 | | 0.3353 | 67.0 | 1675 | 0.5449 | 0.71 | | 0.3353 | 68.0 | 1700 | 0.5461 | 0.71 | | 0.3353 | 69.0 | 1725 | 0.5440 | 0.71 | | 0.3353 | 70.0 | 1750 | 0.5590 | 0.71 | | 0.3353 | 71.0 | 1775 | 0.5391 | 0.71 | | 0.3353 | 72.0 | 1800 | 0.5516 | 0.71 | | 0.3353 | 73.0 | 1825 | 0.5474 | 0.72 | | 0.3353 | 74.0 | 1850 | 0.5477 | 0.72 | | 0.3353 | 75.0 | 1875 | 0.5372 | 0.71 | | 0.3353 | 76.0 | 1900 | 0.5445 | 0.71 | | 0.3353 | 77.0 | 1925 | 0.5421 | 0.71 | | 0.3353 | 78.0 | 1950 | 0.5376 | 0.7 | | 0.3353 | 79.0 | 1975 | 0.5358 | 0.72 | | 0.3108 | 80.0 | 2000 | 0.5369 | 0.72 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3