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20230822105327
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: 0.3487
- Accuracy: 0.4729
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: 0.01
- train_batch_size: 8
- 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 |
---|---|---|---|---|
No log | 1.0 | 312 | 0.6780 | 0.5307 |
0.8761 | 2.0 | 624 | 0.3516 | 0.4982 |
0.8761 | 3.0 | 936 | 0.4775 | 0.4874 |
0.685 | 4.0 | 1248 | 0.3842 | 0.5162 |
0.4946 | 5.0 | 1560 | 0.7400 | 0.5271 |
0.4946 | 6.0 | 1872 | 0.3490 | 0.5307 |
0.5112 | 7.0 | 2184 | 0.4549 | 0.5271 |
0.5112 | 8.0 | 2496 | 0.4590 | 0.4729 |
0.4328 | 9.0 | 2808 | 0.4122 | 0.4729 |
0.5336 | 10.0 | 3120 | 0.3692 | 0.4729 |
0.5336 | 11.0 | 3432 | 0.3493 | 0.5271 |
0.4659 | 12.0 | 3744 | 0.4285 | 0.4729 |
0.4383 | 13.0 | 4056 | 0.3805 | 0.4729 |
0.4383 | 14.0 | 4368 | 0.3634 | 0.5271 |
0.4394 | 15.0 | 4680 | 0.3485 | 0.5271 |
0.4394 | 16.0 | 4992 | 0.4393 | 0.4729 |
0.4432 | 17.0 | 5304 | 0.3694 | 0.5271 |
0.4138 | 18.0 | 5616 | 0.3503 | 0.4874 |
0.4138 | 19.0 | 5928 | 0.3916 | 0.4729 |
0.4213 | 20.0 | 6240 | 0.3495 | 0.4693 |
0.4042 | 21.0 | 6552 | 0.3493 | 0.5090 |
0.4042 | 22.0 | 6864 | 0.3556 | 0.5307 |
0.4177 | 23.0 | 7176 | 0.3697 | 0.4729 |
0.4177 | 24.0 | 7488 | 0.3484 | 0.4765 |
0.3925 | 25.0 | 7800 | 0.3665 | 0.5271 |
0.4006 | 26.0 | 8112 | 0.3669 | 0.5271 |
0.4006 | 27.0 | 8424 | 0.3556 | 0.4729 |
0.397 | 28.0 | 8736 | 0.3529 | 0.4729 |
0.3926 | 29.0 | 9048 | 0.3477 | 0.4729 |
0.3926 | 30.0 | 9360 | 0.5391 | 0.5271 |
0.39 | 31.0 | 9672 | 0.3504 | 0.4729 |
0.39 | 32.0 | 9984 | 0.3494 | 0.5271 |
0.3902 | 33.0 | 10296 | 0.3549 | 0.5271 |
0.3824 | 34.0 | 10608 | 0.3707 | 0.4729 |
0.3824 | 35.0 | 10920 | 0.3559 | 0.4729 |
0.3805 | 36.0 | 11232 | 0.3578 | 0.4729 |
0.38 | 37.0 | 11544 | 0.3612 | 0.5271 |
0.38 | 38.0 | 11856 | 0.3517 | 0.4729 |
0.3784 | 39.0 | 12168 | 0.3487 | 0.4910 |
0.3784 | 40.0 | 12480 | 0.3606 | 0.4729 |
0.3751 | 41.0 | 12792 | 0.3520 | 0.5271 |
0.3718 | 42.0 | 13104 | 0.3477 | 0.5199 |
0.3718 | 43.0 | 13416 | 0.3498 | 0.4729 |
0.371 | 44.0 | 13728 | 0.3729 | 0.4729 |
0.3723 | 45.0 | 14040 | 0.3592 | 0.5271 |
0.3723 | 46.0 | 14352 | 0.3502 | 0.4621 |
0.3688 | 47.0 | 14664 | 0.3516 | 0.4729 |
0.3688 | 48.0 | 14976 | 0.3505 | 0.4729 |
0.3641 | 49.0 | 15288 | 0.3526 | 0.4729 |
0.3645 | 50.0 | 15600 | 0.3488 | 0.4729 |
0.3645 | 51.0 | 15912 | 0.3482 | 0.4729 |
0.3636 | 52.0 | 16224 | 0.3557 | 0.4729 |
0.3621 | 53.0 | 16536 | 0.3484 | 0.4729 |
0.3621 | 54.0 | 16848 | 0.3509 | 0.5271 |
0.3581 | 55.0 | 17160 | 0.3519 | 0.4729 |
0.3581 | 56.0 | 17472 | 0.3479 | 0.5090 |
0.3573 | 57.0 | 17784 | 0.3480 | 0.4729 |
0.3553 | 58.0 | 18096 | 0.3489 | 0.4729 |
0.3553 | 59.0 | 18408 | 0.3479 | 0.4729 |
0.3545 | 60.0 | 18720 | 0.3487 | 0.4729 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3