metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: 1_9e-3_10_0.9
results: []
1_9e-3_10_0.9
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: 0.9482
- Accuracy: 0.7609
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: 0.009
- 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 |
|---|---|---|---|---|
| 5.6057 | 1.0 | 590 | 3.5256 | 0.6080 |
| 4.0044 | 2.0 | 1180 | 5.6686 | 0.6217 |
| 3.6272 | 3.0 | 1770 | 5.5431 | 0.4936 |
| 3.6446 | 4.0 | 2360 | 2.6348 | 0.6174 |
| 3.6031 | 5.0 | 2950 | 2.9075 | 0.6569 |
| 3.7432 | 6.0 | 3540 | 3.3871 | 0.6269 |
| 3.6065 | 7.0 | 4130 | 3.3771 | 0.5746 |
| 3.58 | 8.0 | 4720 | 2.8957 | 0.6584 |
| 3.3121 | 9.0 | 5310 | 8.1931 | 0.6226 |
| 3.01 | 10.0 | 5900 | 2.7215 | 0.6749 |
| 2.6313 | 11.0 | 6490 | 2.0220 | 0.6716 |
| 2.2761 | 12.0 | 7080 | 1.9046 | 0.7021 |
| 2.3338 | 13.0 | 7670 | 1.7751 | 0.7049 |
| 2.0509 | 14.0 | 8260 | 1.7843 | 0.7012 |
| 2.0935 | 15.0 | 8850 | 1.8090 | 0.7220 |
| 1.973 | 16.0 | 9440 | 1.6557 | 0.7306 |
| 1.7967 | 17.0 | 10030 | 1.5804 | 0.7125 |
| 1.6871 | 18.0 | 10620 | 1.4815 | 0.7092 |
| 1.6925 | 19.0 | 11210 | 1.3803 | 0.7361 |
| 1.6661 | 20.0 | 11800 | 1.3541 | 0.7330 |
| 1.6682 | 21.0 | 12390 | 1.5167 | 0.7373 |
| 1.5716 | 22.0 | 12980 | 1.5059 | 0.7257 |
| 1.4106 | 23.0 | 13570 | 1.3936 | 0.7459 |
| 1.355 | 24.0 | 14160 | 1.2851 | 0.7456 |
| 1.3702 | 25.0 | 14750 | 2.6721 | 0.7196 |
| 1.3121 | 26.0 | 15340 | 1.2452 | 0.7434 |
| 1.344 | 27.0 | 15930 | 1.2171 | 0.7477 |
| 1.2869 | 28.0 | 16520 | 1.1749 | 0.7495 |
| 1.2021 | 29.0 | 17110 | 1.1665 | 0.7505 |
| 1.2202 | 30.0 | 17700 | 1.2806 | 0.7593 |
| 1.1704 | 31.0 | 18290 | 1.2779 | 0.7581 |
| 1.134 | 32.0 | 18880 | 1.2130 | 0.7428 |
| 1.1401 | 33.0 | 19470 | 1.2809 | 0.7388 |
| 1.056 | 34.0 | 20060 | 1.1413 | 0.7511 |
| 1.0769 | 35.0 | 20650 | 1.1549 | 0.7459 |
| 1.0196 | 36.0 | 21240 | 1.2625 | 0.7520 |
| 1.0422 | 37.0 | 21830 | 1.3321 | 0.7578 |
| 1.019 | 38.0 | 22420 | 1.2026 | 0.7315 |
| 1.0093 | 39.0 | 23010 | 1.1398 | 0.7480 |
| 1.0076 | 40.0 | 23600 | 1.1515 | 0.7394 |
| 0.943 | 41.0 | 24190 | 1.7801 | 0.7517 |
| 0.9469 | 42.0 | 24780 | 1.0641 | 0.7480 |
| 0.9195 | 43.0 | 25370 | 1.5110 | 0.7569 |
| 0.9116 | 44.0 | 25960 | 1.0370 | 0.7517 |
| 0.9411 | 45.0 | 26550 | 1.0807 | 0.7563 |
| 0.8813 | 46.0 | 27140 | 1.1756 | 0.7633 |
| 0.8775 | 47.0 | 27730 | 1.0464 | 0.7404 |
| 0.8544 | 48.0 | 28320 | 1.0554 | 0.7560 |
| 0.9264 | 49.0 | 28910 | 1.0575 | 0.7456 |
| 0.8571 | 50.0 | 29500 | 1.0595 | 0.7446 |
| 0.8352 | 51.0 | 30090 | 1.1723 | 0.7284 |
| 0.8424 | 52.0 | 30680 | 1.1615 | 0.7642 |
| 0.8264 | 53.0 | 31270 | 1.0357 | 0.7581 |
| 0.7982 | 54.0 | 31860 | 1.0384 | 0.7557 |
| 0.8085 | 55.0 | 32450 | 1.0679 | 0.7336 |
| 0.806 | 56.0 | 33040 | 1.0427 | 0.7645 |
| 0.7658 | 57.0 | 33630 | 1.1823 | 0.7618 |
| 0.7831 | 58.0 | 34220 | 1.1012 | 0.7719 |
| 0.7872 | 59.0 | 34810 | 1.0155 | 0.7636 |
| 0.7976 | 60.0 | 35400 | 0.9905 | 0.7560 |
| 0.7525 | 61.0 | 35990 | 1.1839 | 0.7654 |
| 0.8019 | 62.0 | 36580 | 1.0586 | 0.7697 |
| 0.7394 | 63.0 | 37170 | 1.0845 | 0.7330 |
| 0.7526 | 64.0 | 37760 | 0.9414 | 0.7593 |
| 0.7559 | 65.0 | 38350 | 0.9775 | 0.7483 |
| 0.7389 | 66.0 | 38940 | 0.9854 | 0.7667 |
| 0.7311 | 67.0 | 39530 | 0.9922 | 0.7471 |
| 0.7602 | 68.0 | 40120 | 0.9516 | 0.7523 |
| 0.7174 | 69.0 | 40710 | 0.9789 | 0.7664 |
| 0.7348 | 70.0 | 41300 | 1.1615 | 0.7645 |
| 0.7348 | 71.0 | 41890 | 0.9820 | 0.7535 |
| 0.7364 | 72.0 | 42480 | 0.9867 | 0.7639 |
| 0.6935 | 73.0 | 43070 | 0.9748 | 0.7627 |
| 0.7002 | 74.0 | 43660 | 1.1418 | 0.7691 |
| 0.6987 | 75.0 | 44250 | 1.0109 | 0.7627 |
| 0.6975 | 76.0 | 44840 | 0.9500 | 0.7550 |
| 0.7008 | 77.0 | 45430 | 0.9741 | 0.7621 |
| 0.6976 | 78.0 | 46020 | 1.0055 | 0.7462 |
| 0.7063 | 79.0 | 46610 | 1.0064 | 0.7654 |
| 0.6804 | 80.0 | 47200 | 0.9986 | 0.7661 |
| 0.6574 | 81.0 | 47790 | 0.9993 | 0.7676 |
| 0.6676 | 82.0 | 48380 | 0.9976 | 0.7664 |
| 0.6701 | 83.0 | 48970 | 1.0462 | 0.7709 |
| 0.6589 | 84.0 | 49560 | 1.0222 | 0.7679 |
| 0.6575 | 85.0 | 50150 | 0.9405 | 0.7532 |
| 0.6629 | 86.0 | 50740 | 0.9348 | 0.7529 |
| 0.6634 | 87.0 | 51330 | 1.0199 | 0.7709 |
| 0.6518 | 88.0 | 51920 | 0.9407 | 0.7599 |
| 0.6504 | 89.0 | 52510 | 0.9923 | 0.7661 |
| 0.6294 | 90.0 | 53100 | 0.9581 | 0.7618 |
| 0.6369 | 91.0 | 53690 | 0.9749 | 0.7609 |
| 0.6504 | 92.0 | 54280 | 0.9409 | 0.7550 |
| 0.628 | 93.0 | 54870 | 1.0022 | 0.7667 |
| 0.656 | 94.0 | 55460 | 0.9583 | 0.7606 |
| 0.6251 | 95.0 | 56050 | 0.9518 | 0.7609 |
| 0.6246 | 96.0 | 56640 | 0.9558 | 0.7612 |
| 0.6202 | 97.0 | 57230 | 0.9521 | 0.7602 |
| 0.6179 | 98.0 | 57820 | 0.9481 | 0.7596 |
| 0.6146 | 99.0 | 58410 | 0.9445 | 0.7618 |
| 0.6287 | 100.0 | 59000 | 0.9482 | 0.7609 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3