--- license: apache-2.0 tags: - generated_from_trainer datasets: - super_glue metrics: - accuracy model-index: - name: '20230831185034' results: [] --- # 20230831185034 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: 0.6514 - Accuracy: 0.5 ## 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: 0.0003 - 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 | 340 | 0.6328 | 0.5 | | 0.6373 | 2.0 | 680 | 0.6187 | 0.5 | | 0.6335 | 3.0 | 1020 | 0.6199 | 0.5 | | 0.6335 | 4.0 | 1360 | 0.6402 | 0.5125 | | 0.6141 | 5.0 | 1700 | 0.6342 | 0.5 | | 0.6035 | 6.0 | 2040 | 0.6137 | 0.5 | | 0.6035 | 7.0 | 2380 | 0.6125 | 0.5 | | 0.599 | 8.0 | 2720 | 0.6656 | 0.5 | | 0.6086 | 9.0 | 3060 | 0.6465 | 0.5 | | 0.6086 | 10.0 | 3400 | 0.6109 | 0.5 | | 0.5913 | 11.0 | 3740 | 0.6273 | 0.5 | | 0.5775 | 12.0 | 4080 | 0.6811 | 0.5470 | | 0.5775 | 13.0 | 4420 | 0.6180 | 0.5 | | 0.5687 | 14.0 | 4760 | 0.6692 | 0.5 | | 0.5668 | 15.0 | 5100 | 0.6105 | 0.5 | | 0.5668 | 16.0 | 5440 | 0.6322 | 0.5 | | 0.5643 | 17.0 | 5780 | 0.6456 | 0.5313 | | 0.5529 | 18.0 | 6120 | 0.6209 | 0.5 | | 0.5529 | 19.0 | 6460 | 0.6351 | 0.5 | | 0.5533 | 20.0 | 6800 | 0.6468 | 0.5 | | 0.5494 | 21.0 | 7140 | 0.6303 | 0.5 | | 0.5494 | 22.0 | 7480 | 0.6105 | 0.5 | | 0.5514 | 23.0 | 7820 | 0.6282 | 0.5 | | 0.54 | 24.0 | 8160 | 0.6196 | 0.5 | | 0.541 | 25.0 | 8500 | 0.6838 | 0.5 | | 0.541 | 26.0 | 8840 | 0.6171 | 0.5 | | 0.5378 | 27.0 | 9180 | 0.6537 | 0.5 | | 0.5344 | 28.0 | 9520 | 0.6543 | 0.5 | | 0.5344 | 29.0 | 9860 | 0.6515 | 0.5 | | 0.5303 | 30.0 | 10200 | 0.6314 | 0.5 | | 0.5284 | 31.0 | 10540 | 0.6371 | 0.5 | | 0.5284 | 32.0 | 10880 | 0.6739 | 0.5 | | 0.5252 | 33.0 | 11220 | 0.6632 | 0.5 | | 0.5232 | 34.0 | 11560 | 0.6564 | 0.5 | | 0.5232 | 35.0 | 11900 | 0.6271 | 0.5 | | 0.521 | 36.0 | 12240 | 0.6306 | 0.5 | | 0.5215 | 37.0 | 12580 | 0.6324 | 0.5 | | 0.5215 | 38.0 | 12920 | 0.7030 | 0.4984 | | 0.5177 | 39.0 | 13260 | 0.6432 | 0.5 | | 0.5136 | 40.0 | 13600 | 0.6151 | 0.5 | | 0.5136 | 41.0 | 13940 | 0.6601 | 0.5 | | 0.5153 | 42.0 | 14280 | 0.6176 | 0.5 | | 0.5114 | 43.0 | 14620 | 0.6579 | 0.5 | | 0.5114 | 44.0 | 14960 | 0.6584 | 0.5 | | 0.514 | 45.0 | 15300 | 0.6408 | 0.5 | | 0.5093 | 46.0 | 15640 | 0.6490 | 0.5 | | 0.5093 | 47.0 | 15980 | 0.6457 | 0.5 | | 0.5105 | 48.0 | 16320 | 0.6642 | 0.5 | | 0.5067 | 49.0 | 16660 | 0.6358 | 0.5 | | 0.5069 | 50.0 | 17000 | 0.6318 | 0.5 | | 0.5069 | 51.0 | 17340 | 0.6718 | 0.5 | | 0.5059 | 52.0 | 17680 | 0.6658 | 0.5 | | 0.5064 | 53.0 | 18020 | 0.6414 | 0.5 | | 0.5064 | 54.0 | 18360 | 0.6285 | 0.5 | | 0.5034 | 55.0 | 18700 | 0.6793 | 0.5 | | 0.4992 | 56.0 | 19040 | 0.6790 | 0.5 | | 0.4992 | 57.0 | 19380 | 0.6370 | 0.5 | | 0.5013 | 58.0 | 19720 | 0.6795 | 0.5 | | 0.5015 | 59.0 | 20060 | 0.6312 | 0.5 | | 0.5015 | 60.0 | 20400 | 0.6487 | 0.5 | | 0.4984 | 61.0 | 20740 | 0.6539 | 0.5 | | 0.499 | 62.0 | 21080 | 0.6254 | 0.5 | | 0.499 | 63.0 | 21420 | 0.6403 | 0.5 | | 0.4977 | 64.0 | 21760 | 0.6619 | 0.5 | | 0.4992 | 65.0 | 22100 | 0.6459 | 0.5 | | 0.4992 | 66.0 | 22440 | 0.6428 | 0.5 | | 0.4899 | 67.0 | 22780 | 0.6488 | 0.5 | | 0.5006 | 68.0 | 23120 | 0.6486 | 0.5 | | 0.5006 | 69.0 | 23460 | 0.6512 | 0.5 | | 0.4971 | 70.0 | 23800 | 0.6509 | 0.5 | | 0.496 | 71.0 | 24140 | 0.6758 | 0.5 | | 0.496 | 72.0 | 24480 | 0.6587 | 0.5 | | 0.49 | 73.0 | 24820 | 0.6529 | 0.5 | | 0.4939 | 74.0 | 25160 | 0.6659 | 0.5 | | 0.492 | 75.0 | 25500 | 0.6504 | 0.5 | | 0.492 | 76.0 | 25840 | 0.6531 | 0.5 | | 0.4934 | 77.0 | 26180 | 0.6529 | 0.5 | | 0.491 | 78.0 | 26520 | 0.6498 | 0.5 | | 0.491 | 79.0 | 26860 | 0.6515 | 0.5 | | 0.4895 | 80.0 | 27200 | 0.6514 | 0.5 | ### Framework versions - Transformers 4.26.1 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3