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20230824043649
This model is a fine-tuned version of bert-large-cased on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.0771
- Accuracy: 0.7365
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: 4
- 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 |
---|---|---|---|---|
0.4513 | 1.0 | 623 | 0.4036 | 0.4729 |
0.321 | 2.0 | 1246 | 0.3454 | 0.4729 |
0.339 | 3.0 | 1869 | 0.1727 | 0.5271 |
0.3594 | 4.0 | 2492 | 0.4321 | 0.4729 |
0.3103 | 5.0 | 3115 | 0.2311 | 0.5415 |
0.3042 | 6.0 | 3738 | 0.1428 | 0.6679 |
0.2996 | 7.0 | 4361 | 0.2423 | 0.5668 |
0.274 | 8.0 | 4984 | 0.1331 | 0.6895 |
0.2824 | 9.0 | 5607 | 0.1173 | 0.6931 |
0.2458 | 10.0 | 6230 | 0.1350 | 0.6968 |
0.2005 | 11.0 | 6853 | 0.1456 | 0.5884 |
0.1689 | 12.0 | 7476 | 0.1289 | 0.6787 |
0.1644 | 13.0 | 8099 | 0.1109 | 0.6931 |
0.1578 | 14.0 | 8722 | 0.1143 | 0.7040 |
0.1502 | 15.0 | 9345 | 0.1178 | 0.6968 |
0.141 | 16.0 | 9968 | 0.0974 | 0.6968 |
0.1365 | 17.0 | 10591 | 0.0980 | 0.6787 |
0.1327 | 18.0 | 11214 | 0.1128 | 0.6931 |
0.1352 | 19.0 | 11837 | 0.1543 | 0.6390 |
0.1324 | 20.0 | 12460 | 0.0938 | 0.7184 |
0.1274 | 21.0 | 13083 | 0.0907 | 0.7112 |
0.1244 | 22.0 | 13706 | 0.1093 | 0.7112 |
0.1227 | 23.0 | 14329 | 0.1061 | 0.7076 |
0.1142 | 24.0 | 14952 | 0.0972 | 0.7112 |
0.1094 | 25.0 | 15575 | 0.0872 | 0.7184 |
0.1099 | 26.0 | 16198 | 0.0904 | 0.7292 |
0.1086 | 27.0 | 16821 | 0.0912 | 0.7040 |
0.1083 | 28.0 | 17444 | 0.0850 | 0.7148 |
0.1061 | 29.0 | 18067 | 0.0832 | 0.7184 |
0.1008 | 30.0 | 18690 | 0.0951 | 0.7292 |
0.1036 | 31.0 | 19313 | 0.0879 | 0.7220 |
0.1024 | 32.0 | 19936 | 0.0850 | 0.7220 |
0.0945 | 33.0 | 20559 | 0.0828 | 0.7220 |
0.0961 | 34.0 | 21182 | 0.0838 | 0.7329 |
0.0935 | 35.0 | 21805 | 0.0814 | 0.7256 |
0.097 | 36.0 | 22428 | 0.0812 | 0.7329 |
0.0925 | 37.0 | 23051 | 0.0810 | 0.7292 |
0.0911 | 38.0 | 23674 | 0.0826 | 0.7256 |
0.0855 | 39.0 | 24297 | 0.0815 | 0.7329 |
0.0895 | 40.0 | 24920 | 0.0826 | 0.7329 |
0.0847 | 41.0 | 25543 | 0.0821 | 0.7292 |
0.0864 | 42.0 | 26166 | 0.0797 | 0.7292 |
0.0848 | 43.0 | 26789 | 0.0823 | 0.7256 |
0.0817 | 44.0 | 27412 | 0.0791 | 0.7329 |
0.0829 | 45.0 | 28035 | 0.0795 | 0.7220 |
0.0826 | 46.0 | 28658 | 0.0789 | 0.7365 |
0.0816 | 47.0 | 29281 | 0.0783 | 0.7220 |
0.0821 | 48.0 | 29904 | 0.0796 | 0.7437 |
0.0798 | 49.0 | 30527 | 0.0800 | 0.7220 |
0.0782 | 50.0 | 31150 | 0.0784 | 0.7437 |
0.079 | 51.0 | 31773 | 0.0784 | 0.7401 |
0.0797 | 52.0 | 32396 | 0.0795 | 0.7329 |
0.0804 | 53.0 | 33019 | 0.0784 | 0.7365 |
0.0762 | 54.0 | 33642 | 0.0770 | 0.7329 |
0.0727 | 55.0 | 34265 | 0.0777 | 0.7365 |
0.0749 | 56.0 | 34888 | 0.0786 | 0.7329 |
0.0737 | 57.0 | 35511 | 0.0773 | 0.7292 |
0.0734 | 58.0 | 36134 | 0.0776 | 0.7292 |
0.0737 | 59.0 | 36757 | 0.0777 | 0.7365 |
0.0736 | 60.0 | 37380 | 0.0771 | 0.7365 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3