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20230822120451
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: 11.7866
- 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: 0.004
- 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 | 13.5886 | 0.5271 |
18.7749 | 2.0 | 624 | 13.1889 | 0.4729 |
18.7749 | 3.0 | 936 | 12.7687 | 0.4729 |
17.8689 | 4.0 | 1248 | 12.3773 | 0.4729 |
17.738 | 5.0 | 1560 | 12.5498 | 0.4729 |
17.738 | 6.0 | 1872 | 12.3920 | 0.4729 |
17.7159 | 7.0 | 2184 | 12.3910 | 0.4729 |
17.7159 | 8.0 | 2496 | 12.3585 | 0.4729 |
17.6431 | 9.0 | 2808 | 12.3978 | 0.4729 |
17.5993 | 10.0 | 3120 | 12.2603 | 0.4729 |
17.5993 | 11.0 | 3432 | 12.1054 | 0.4729 |
17.5276 | 12.0 | 3744 | 12.1379 | 0.5271 |
17.4675 | 13.0 | 4056 | 12.0354 | 0.5271 |
17.4675 | 14.0 | 4368 | 12.0828 | 0.5271 |
17.4824 | 15.0 | 4680 | 11.9830 | 0.5271 |
17.4824 | 16.0 | 4992 | 12.0574 | 0.4729 |
17.4065 | 17.0 | 5304 | 12.7325 | 0.5271 |
17.4328 | 18.0 | 5616 | 12.0570 | 0.4729 |
17.4328 | 19.0 | 5928 | 12.0770 | 0.4729 |
17.3925 | 20.0 | 6240 | 12.0314 | 0.5271 |
17.3467 | 21.0 | 6552 | 11.9670 | 0.5271 |
17.3467 | 22.0 | 6864 | 12.1346 | 0.5271 |
17.3575 | 23.0 | 7176 | 12.4856 | 0.4729 |
17.3575 | 24.0 | 7488 | 12.8699 | 0.4729 |
17.3374 | 25.0 | 7800 | 11.9199 | 0.5307 |
17.3162 | 26.0 | 8112 | 11.9558 | 0.5271 |
17.3162 | 27.0 | 8424 | 11.9757 | 0.5271 |
17.307 | 28.0 | 8736 | 12.2557 | 0.4729 |
17.2934 | 29.0 | 9048 | 11.8987 | 0.4729 |
17.2934 | 30.0 | 9360 | 12.1451 | 0.5271 |
17.2734 | 31.0 | 9672 | 11.9358 | 0.5271 |
17.2734 | 32.0 | 9984 | 11.9698 | 0.5271 |
17.2631 | 33.0 | 10296 | 11.9269 | 0.4729 |
17.2612 | 34.0 | 10608 | 11.9251 | 0.5271 |
17.2612 | 35.0 | 10920 | 11.9818 | 0.4729 |
17.2473 | 36.0 | 11232 | 12.0614 | 0.4729 |
17.2419 | 37.0 | 11544 | 11.8218 | 0.5271 |
17.2419 | 38.0 | 11856 | 11.8899 | 0.4729 |
17.2188 | 39.0 | 12168 | 11.8847 | 0.5271 |
17.2188 | 40.0 | 12480 | 11.8971 | 0.4729 |
17.2216 | 41.0 | 12792 | 11.8868 | 0.5271 |
17.2037 | 42.0 | 13104 | 11.8386 | 0.4729 |
17.2037 | 43.0 | 13416 | 11.8261 | 0.4729 |
17.2027 | 44.0 | 13728 | 11.8480 | 0.4729 |
17.181 | 45.0 | 14040 | 11.9217 | 0.5271 |
17.181 | 46.0 | 14352 | 11.8834 | 0.4729 |
17.1823 | 47.0 | 14664 | 11.8595 | 0.4729 |
17.1823 | 48.0 | 14976 | 11.8201 | 0.5271 |
17.1721 | 49.0 | 15288 | 11.8889 | 0.4729 |
17.168 | 50.0 | 15600 | 11.8029 | 0.5271 |
17.168 | 51.0 | 15912 | 11.8118 | 0.4729 |
17.1493 | 52.0 | 16224 | 11.7825 | 0.4729 |
17.1493 | 53.0 | 16536 | 11.8072 | 0.5271 |
17.1493 | 54.0 | 16848 | 11.8041 | 0.5271 |
17.1256 | 55.0 | 17160 | 11.8140 | 0.4729 |
17.1256 | 56.0 | 17472 | 11.8077 | 0.5271 |
17.1315 | 57.0 | 17784 | 11.8012 | 0.5271 |
17.1204 | 58.0 | 18096 | 11.7970 | 0.4729 |
17.1204 | 59.0 | 18408 | 11.7870 | 0.5271 |
17.1129 | 60.0 | 18720 | 11.7866 | 0.4729 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3