20230823054903
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: 0.0697
- Accuracy: 0.5271
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: 0.004
- 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 | 0.0788 | 0.5271 |
| 0.1715 | 2.0 | 624 | 0.2059 | 0.4729 |
| 0.1715 | 3.0 | 936 | 0.1134 | 0.4729 |
| 0.1222 | 4.0 | 1248 | 0.0831 | 0.5343 |
| 0.1187 | 5.0 | 1560 | 0.0732 | 0.5704 |
| 0.1187 | 6.0 | 1872 | 0.0796 | 0.4729 |
| 0.0991 | 7.0 | 2184 | 0.0745 | 0.4729 |
| 0.0991 | 8.0 | 2496 | 0.0716 | 0.4982 |
| 0.0819 | 9.0 | 2808 | 0.0705 | 0.4910 |
| 0.0807 | 10.0 | 3120 | 0.0702 | 0.4765 |
| 0.0807 | 11.0 | 3432 | 0.0713 | 0.4729 |
| 0.0802 | 12.0 | 3744 | 0.0703 | 0.4729 |
| 0.0795 | 13.0 | 4056 | 0.0784 | 0.4729 |
| 0.0795 | 14.0 | 4368 | 0.0706 | 0.5307 |
| 0.0794 | 15.0 | 4680 | 0.0730 | 0.4729 |
| 0.0794 | 16.0 | 4992 | 0.0706 | 0.4801 |
| 0.0806 | 17.0 | 5304 | 0.0711 | 0.5596 |
| 0.0811 | 18.0 | 5616 | 0.0704 | 0.4693 |
| 0.0811 | 19.0 | 5928 | 0.0701 | 0.4874 |
| 0.0798 | 20.0 | 6240 | 0.0719 | 0.6101 |
| 0.0793 | 21.0 | 6552 | 0.0705 | 0.4693 |
| 0.0793 | 22.0 | 6864 | 0.0707 | 0.5884 |
| 0.0795 | 23.0 | 7176 | 0.0712 | 0.4729 |
| 0.0795 | 24.0 | 7488 | 0.0705 | 0.4729 |
| 0.0796 | 25.0 | 7800 | 0.0789 | 0.5271 |
| 0.0796 | 26.0 | 8112 | 0.0705 | 0.4801 |
| 0.0796 | 27.0 | 8424 | 0.0703 | 0.4765 |
| 0.0787 | 28.0 | 8736 | 0.0703 | 0.4838 |
| 0.079 | 29.0 | 9048 | 0.0716 | 0.4729 |
| 0.079 | 30.0 | 9360 | 0.0739 | 0.5704 |
| 0.0788 | 31.0 | 9672 | 0.0749 | 0.5632 |
| 0.0788 | 32.0 | 9984 | 0.0711 | 0.4729 |
| 0.0789 | 33.0 | 10296 | 0.0705 | 0.4838 |
| 0.0786 | 34.0 | 10608 | 0.0700 | 0.5199 |
| 0.0786 | 35.0 | 10920 | 0.0699 | 0.4838 |
| 0.0785 | 36.0 | 11232 | 0.0715 | 0.4729 |
| 0.0784 | 37.0 | 11544 | 0.0716 | 0.6354 |
| 0.0784 | 38.0 | 11856 | 0.0719 | 0.4729 |
| 0.0781 | 39.0 | 12168 | 0.0700 | 0.5487 |
| 0.0781 | 40.0 | 12480 | 0.0700 | 0.5848 |
| 0.0778 | 41.0 | 12792 | 0.0704 | 0.6173 |
| 0.0778 | 42.0 | 13104 | 0.0705 | 0.5848 |
| 0.0778 | 43.0 | 13416 | 0.0705 | 0.6209 |
| 0.078 | 44.0 | 13728 | 0.0701 | 0.5199 |
| 0.0776 | 45.0 | 14040 | 0.0704 | 0.5957 |
| 0.0776 | 46.0 | 14352 | 0.0702 | 0.5848 |
| 0.0772 | 47.0 | 14664 | 0.0703 | 0.4765 |
| 0.0772 | 48.0 | 14976 | 0.0697 | 0.5379 |
| 0.0773 | 49.0 | 15288 | 0.0696 | 0.5596 |
| 0.0772 | 50.0 | 15600 | 0.0702 | 0.4765 |
| 0.0772 | 51.0 | 15912 | 0.0701 | 0.4801 |
| 0.0776 | 52.0 | 16224 | 0.0706 | 0.4729 |
| 0.0772 | 53.0 | 16536 | 0.0698 | 0.5054 |
| 0.0772 | 54.0 | 16848 | 0.0706 | 0.6318 |
| 0.0766 | 55.0 | 17160 | 0.0708 | 0.4765 |
| 0.0766 | 56.0 | 17472 | 0.0700 | 0.6209 |
| 0.0766 | 57.0 | 17784 | 0.0697 | 0.5307 |
| 0.0767 | 58.0 | 18096 | 0.0700 | 0.4801 |
| 0.0767 | 59.0 | 18408 | 0.0697 | 0.5235 |
| 0.0767 | 60.0 | 18720 | 0.0697 | 0.5271 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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