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20230824210912
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: 1.0575
- Accuracy: 0.7401
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: 0.005
- 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 | 156 | 0.8273 | 0.5307 |
| No log | 2.0 | 312 | 1.1309 | 0.4729 |
| No log | 3.0 | 468 | 0.8140 | 0.4765 |
| 0.9525 | 4.0 | 624 | 0.6978 | 0.5776 |
| 0.9525 | 5.0 | 780 | 0.6845 | 0.5704 |
| 0.9525 | 6.0 | 936 | 0.6365 | 0.6282 |
| 0.8192 | 7.0 | 1092 | 0.8362 | 0.6354 |
| 0.8192 | 8.0 | 1248 | 0.5976 | 0.6859 |
| 0.8192 | 9.0 | 1404 | 0.6788 | 0.6751 |
| 0.7543 | 10.0 | 1560 | 0.6672 | 0.6606 |
| 0.7543 | 11.0 | 1716 | 0.6932 | 0.5776 |
| 0.7543 | 12.0 | 1872 | 0.6756 | 0.6895 |
| 0.6718 | 13.0 | 2028 | 0.6336 | 0.7292 |
| 0.6718 | 14.0 | 2184 | 0.6149 | 0.7256 |
| 0.6718 | 15.0 | 2340 | 0.7579 | 0.6570 |
| 0.6718 | 16.0 | 2496 | 0.8701 | 0.6137 |
| 0.6043 | 17.0 | 2652 | 0.5931 | 0.7256 |
| 0.6043 | 18.0 | 2808 | 0.5982 | 0.7256 |
| 0.6043 | 19.0 | 2964 | 0.6829 | 0.7148 |
| 0.5842 | 20.0 | 3120 | 1.3393 | 0.6354 |
| 0.5842 | 21.0 | 3276 | 0.7701 | 0.6823 |
| 0.5842 | 22.0 | 3432 | 0.7801 | 0.6679 |
| 0.5907 | 23.0 | 3588 | 0.6225 | 0.7401 |
| 0.5907 | 24.0 | 3744 | 0.7348 | 0.7292 |
| 0.5907 | 25.0 | 3900 | 0.7832 | 0.6859 |
| 0.5013 | 26.0 | 4056 | 0.5946 | 0.7329 |
| 0.5013 | 27.0 | 4212 | 0.6441 | 0.7365 |
| 0.5013 | 28.0 | 4368 | 0.6992 | 0.7112 |
| 0.4569 | 29.0 | 4524 | 0.8007 | 0.7329 |
| 0.4569 | 30.0 | 4680 | 1.1460 | 0.6643 |
| 0.4569 | 31.0 | 4836 | 1.1331 | 0.6606 |
| 0.4569 | 32.0 | 4992 | 0.7750 | 0.7220 |
| 0.4256 | 33.0 | 5148 | 0.8709 | 0.7256 |
| 0.4256 | 34.0 | 5304 | 0.8764 | 0.7184 |
| 0.4256 | 35.0 | 5460 | 0.8154 | 0.7256 |
| 0.3773 | 36.0 | 5616 | 0.8308 | 0.7329 |
| 0.3773 | 37.0 | 5772 | 0.8417 | 0.7184 |
| 0.3773 | 38.0 | 5928 | 1.1260 | 0.7401 |
| 0.3676 | 39.0 | 6084 | 0.8739 | 0.7401 |
| 0.3676 | 40.0 | 6240 | 0.7295 | 0.7509 |
| 0.3676 | 41.0 | 6396 | 1.0227 | 0.7220 |
| 0.3122 | 42.0 | 6552 | 1.2354 | 0.7184 |
| 0.3122 | 43.0 | 6708 | 0.9760 | 0.7401 |
| 0.3122 | 44.0 | 6864 | 0.8684 | 0.7329 |
| 0.3011 | 45.0 | 7020 | 0.9423 | 0.7545 |
| 0.3011 | 46.0 | 7176 | 1.0446 | 0.7401 |
| 0.3011 | 47.0 | 7332 | 1.2442 | 0.7256 |
| 0.3011 | 48.0 | 7488 | 0.8938 | 0.7292 |
| 0.2606 | 49.0 | 7644 | 1.0857 | 0.7220 |
| 0.2606 | 50.0 | 7800 | 1.1683 | 0.7148 |
| 0.2606 | 51.0 | 7956 | 0.9944 | 0.7220 |
| 0.2496 | 52.0 | 8112 | 0.9914 | 0.7401 |
| 0.2496 | 53.0 | 8268 | 1.0398 | 0.7365 |
| 0.2496 | 54.0 | 8424 | 1.2414 | 0.7256 |
| 0.2293 | 55.0 | 8580 | 1.0096 | 0.7220 |
| 0.2293 | 56.0 | 8736 | 0.9548 | 0.7365 |
| 0.2293 | 57.0 | 8892 | 1.2170 | 0.7220 |
| 0.2182 | 58.0 | 9048 | 1.1249 | 0.7220 |
| 0.2182 | 59.0 | 9204 | 1.1084 | 0.7292 |
| 0.2182 | 60.0 | 9360 | 1.0558 | 0.7292 |
| 0.2111 | 61.0 | 9516 | 1.1070 | 0.7292 |
| 0.2111 | 62.0 | 9672 | 1.1918 | 0.7473 |
| 0.2111 | 63.0 | 9828 | 1.1819 | 0.7220 |
| 0.2111 | 64.0 | 9984 | 1.1041 | 0.7437 |
| 0.2024 | 65.0 | 10140 | 1.2129 | 0.7184 |
| 0.2024 | 66.0 | 10296 | 1.0185 | 0.7437 |
| 0.2024 | 67.0 | 10452 | 0.9763 | 0.7437 |
| 0.1901 | 68.0 | 10608 | 1.0053 | 0.7292 |
| 0.1901 | 69.0 | 10764 | 1.1605 | 0.7292 |
| 0.1901 | 70.0 | 10920 | 1.3683 | 0.7220 |
| 0.1843 | 71.0 | 11076 | 1.0427 | 0.7365 |
| 0.1843 | 72.0 | 11232 | 1.1283 | 0.7437 |
| 0.1843 | 73.0 | 11388 | 1.0405 | 0.7473 |
| 0.1715 | 74.0 | 11544 | 0.9890 | 0.7509 |
| 0.1715 | 75.0 | 11700 | 1.2353 | 0.7329 |
| 0.1715 | 76.0 | 11856 | 1.0175 | 0.7365 |
| 0.1698 | 77.0 | 12012 | 1.0641 | 0.7365 |
| 0.1698 | 78.0 | 12168 | 1.0655 | 0.7292 |
| 0.1698 | 79.0 | 12324 | 1.0779 | 0.7329 |
| 0.1698 | 80.0 | 12480 | 1.0575 | 0.7401 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
