metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: 1_8e-3_10_0.1
results: []
1_8e-3_10_0.1
This model is a fine-tuned version of bert-large-uncased on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.0109
- Accuracy: 0.7272
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: 0.008
- 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: 100.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.8619 | 1.0 | 590 | 1.0251 | 0.4685 |
1.3275 | 2.0 | 1180 | 1.3329 | 0.3795 |
1.2711 | 3.0 | 1770 | 1.3427 | 0.3817 |
1.2563 | 4.0 | 2360 | 0.9486 | 0.6352 |
1.3677 | 5.0 | 2950 | 1.5968 | 0.4266 |
1.2101 | 6.0 | 3540 | 2.8999 | 0.6217 |
1.2131 | 7.0 | 4130 | 1.7592 | 0.4410 |
1.0951 | 8.0 | 4720 | 1.0889 | 0.6535 |
1.1265 | 9.0 | 5310 | 1.6306 | 0.4963 |
1.0834 | 10.0 | 5900 | 0.8228 | 0.6789 |
0.9934 | 11.0 | 6490 | 0.9519 | 0.6789 |
0.9867 | 12.0 | 7080 | 1.2001 | 0.6471 |
0.9321 | 13.0 | 7670 | 0.7980 | 0.6850 |
0.914 | 14.0 | 8260 | 0.7659 | 0.7092 |
0.9005 | 15.0 | 8850 | 0.8234 | 0.7104 |
0.8728 | 16.0 | 9440 | 0.9553 | 0.6948 |
0.7346 | 17.0 | 10030 | 2.0394 | 0.5012 |
0.8001 | 18.0 | 10620 | 1.2116 | 0.6180 |
0.8778 | 19.0 | 11210 | 0.8516 | 0.6823 |
0.7117 | 20.0 | 11800 | 1.1178 | 0.6251 |
0.6709 | 21.0 | 12390 | 0.8929 | 0.7125 |
0.7554 | 22.0 | 12980 | 0.9317 | 0.6801 |
0.7167 | 23.0 | 13570 | 1.3876 | 0.6061 |
0.6239 | 24.0 | 14160 | 0.9124 | 0.6737 |
0.6273 | 25.0 | 14750 | 0.8818 | 0.7242 |
0.5882 | 26.0 | 15340 | 1.0614 | 0.6728 |
0.5567 | 27.0 | 15930 | 1.0177 | 0.7306 |
0.5606 | 28.0 | 16520 | 1.3018 | 0.6459 |
0.5559 | 29.0 | 17110 | 1.4926 | 0.6914 |
0.4879 | 30.0 | 17700 | 0.9648 | 0.6924 |
0.4945 | 31.0 | 18290 | 0.9028 | 0.7150 |
0.4876 | 32.0 | 18880 | 0.8188 | 0.7257 |
0.455 | 33.0 | 19470 | 1.0325 | 0.7312 |
0.468 | 34.0 | 20060 | 0.9495 | 0.7330 |
0.4324 | 35.0 | 20650 | 0.8765 | 0.7202 |
0.4098 | 36.0 | 21240 | 1.5105 | 0.6963 |
0.4002 | 37.0 | 21830 | 0.9019 | 0.7309 |
0.4077 | 38.0 | 22420 | 0.8470 | 0.7223 |
0.378 | 39.0 | 23010 | 0.9477 | 0.7196 |
0.3697 | 40.0 | 23600 | 0.9213 | 0.7226 |
0.3957 | 41.0 | 24190 | 0.9321 | 0.7260 |
0.338 | 42.0 | 24780 | 0.8633 | 0.7284 |
0.343 | 43.0 | 25370 | 0.9502 | 0.7355 |
0.3454 | 44.0 | 25960 | 1.1264 | 0.6930 |
0.3288 | 45.0 | 26550 | 1.5310 | 0.6440 |
0.3075 | 46.0 | 27140 | 1.0321 | 0.7067 |
0.326 | 47.0 | 27730 | 1.0041 | 0.7257 |
0.3035 | 48.0 | 28320 | 0.9984 | 0.7168 |
0.3318 | 49.0 | 28910 | 0.9336 | 0.7294 |
0.2923 | 50.0 | 29500 | 1.2029 | 0.6758 |
0.2813 | 51.0 | 30090 | 0.9525 | 0.7217 |
0.2844 | 52.0 | 30680 | 1.0021 | 0.7242 |
0.2706 | 53.0 | 31270 | 0.9836 | 0.7187 |
0.2748 | 54.0 | 31860 | 0.9966 | 0.7113 |
0.2585 | 55.0 | 32450 | 1.0029 | 0.7211 |
0.2603 | 56.0 | 33040 | 0.9700 | 0.7235 |
0.2442 | 57.0 | 33630 | 0.9675 | 0.7330 |
0.2503 | 58.0 | 34220 | 1.0088 | 0.7373 |
0.2473 | 59.0 | 34810 | 0.9043 | 0.7306 |
0.2503 | 60.0 | 35400 | 1.0069 | 0.7211 |
0.233 | 61.0 | 35990 | 1.0046 | 0.7245 |
0.2248 | 62.0 | 36580 | 1.0468 | 0.7217 |
0.2343 | 63.0 | 37170 | 0.9263 | 0.7202 |
0.2312 | 64.0 | 37760 | 1.1075 | 0.7101 |
0.2173 | 65.0 | 38350 | 1.0439 | 0.7205 |
0.2138 | 66.0 | 38940 | 1.1012 | 0.7364 |
0.2037 | 67.0 | 39530 | 1.0094 | 0.7336 |
0.2129 | 68.0 | 40120 | 0.9811 | 0.7275 |
0.1937 | 69.0 | 40710 | 1.0312 | 0.7419 |
0.2102 | 70.0 | 41300 | 1.0208 | 0.7318 |
0.2078 | 71.0 | 41890 | 1.0093 | 0.7174 |
0.2037 | 72.0 | 42480 | 1.1041 | 0.7404 |
0.1903 | 73.0 | 43070 | 0.9927 | 0.7318 |
0.1898 | 74.0 | 43660 | 1.0875 | 0.7431 |
0.1966 | 75.0 | 44250 | 0.9659 | 0.7257 |
0.1967 | 76.0 | 44840 | 1.0025 | 0.7254 |
0.191 | 77.0 | 45430 | 0.9488 | 0.7306 |
0.1916 | 78.0 | 46020 | 1.0042 | 0.7327 |
0.1819 | 79.0 | 46610 | 1.0258 | 0.7355 |
0.1794 | 80.0 | 47200 | 1.0124 | 0.7309 |
0.1773 | 81.0 | 47790 | 0.9920 | 0.7324 |
0.1852 | 82.0 | 48380 | 1.0088 | 0.7367 |
0.1809 | 83.0 | 48970 | 1.0702 | 0.7352 |
0.1695 | 84.0 | 49560 | 1.0249 | 0.7260 |
0.1704 | 85.0 | 50150 | 1.0086 | 0.7294 |
0.1698 | 86.0 | 50740 | 1.0465 | 0.7318 |
0.1609 | 87.0 | 51330 | 1.0387 | 0.7291 |
0.1654 | 88.0 | 51920 | 1.0260 | 0.7297 |
0.1589 | 89.0 | 52510 | 1.0342 | 0.7257 |
0.1624 | 90.0 | 53100 | 1.0773 | 0.7297 |
0.1633 | 91.0 | 53690 | 1.0567 | 0.7309 |
0.1593 | 92.0 | 54280 | 1.0176 | 0.7196 |
0.1558 | 93.0 | 54870 | 1.0428 | 0.7257 |
0.1536 | 94.0 | 55460 | 1.0158 | 0.7294 |
0.1559 | 95.0 | 56050 | 1.0159 | 0.7315 |
0.1577 | 96.0 | 56640 | 1.0299 | 0.7306 |
0.1518 | 97.0 | 57230 | 1.0132 | 0.7281 |
0.1477 | 98.0 | 57820 | 0.9931 | 0.7266 |
0.1529 | 99.0 | 58410 | 1.0248 | 0.7272 |
0.1445 | 100.0 | 59000 | 1.0109 | 0.7272 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3