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20230825024137
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: 0.5934
- Accuracy: 0.7545
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: 0.005
- 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: 80.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 156 | 0.7579 | 0.5307 |
| No log | 2.0 | 312 | 0.8311 | 0.4838 |
| No log | 3.0 | 468 | 0.8071 | 0.4838 |
| 0.9372 | 4.0 | 624 | 0.6483 | 0.5632 |
| 0.9372 | 5.0 | 780 | 0.6240 | 0.5740 |
| 0.9372 | 6.0 | 936 | 0.6779 | 0.5343 |
| 0.9135 | 7.0 | 1092 | 0.8693 | 0.5632 |
| 0.9135 | 8.0 | 1248 | 0.6308 | 0.6245 |
| 0.9135 | 9.0 | 1404 | 0.6566 | 0.6462 |
| 0.7837 | 10.0 | 1560 | 0.5220 | 0.6787 |
| 0.7837 | 11.0 | 1716 | 0.6467 | 0.6390 |
| 0.7837 | 12.0 | 1872 | 0.5238 | 0.7220 |
| 0.6625 | 13.0 | 2028 | 0.5079 | 0.7040 |
| 0.6625 | 14.0 | 2184 | 0.5625 | 0.7148 |
| 0.6625 | 15.0 | 2340 | 0.4786 | 0.7148 |
| 0.6625 | 16.0 | 2496 | 0.7720 | 0.6426 |
| 0.6308 | 17.0 | 2652 | 0.4866 | 0.7004 |
| 0.6308 | 18.0 | 2808 | 0.4569 | 0.7329 |
| 0.6308 | 19.0 | 2964 | 0.4564 | 0.7329 |
| 0.6613 | 20.0 | 3120 | 0.6097 | 0.6823 |
| 0.6613 | 21.0 | 3276 | 0.5519 | 0.7112 |
| 0.6613 | 22.0 | 3432 | 0.6481 | 0.6679 |
| 0.5641 | 23.0 | 3588 | 0.5730 | 0.7040 |
| 0.5641 | 24.0 | 3744 | 0.5306 | 0.7076 |
| 0.5641 | 25.0 | 3900 | 0.9908 | 0.6606 |
| 0.5287 | 26.0 | 4056 | 0.4475 | 0.7545 |
| 0.5287 | 27.0 | 4212 | 0.4697 | 0.7473 |
| 0.5287 | 28.0 | 4368 | 0.5206 | 0.7040 |
| 0.5013 | 29.0 | 4524 | 0.4780 | 0.7401 |
| 0.5013 | 30.0 | 4680 | 0.6273 | 0.6787 |
| 0.5013 | 31.0 | 4836 | 0.6055 | 0.7076 |
| 0.5013 | 32.0 | 4992 | 0.4938 | 0.7401 |
| 0.4549 | 33.0 | 5148 | 0.5795 | 0.6931 |
| 0.4549 | 34.0 | 5304 | 0.5363 | 0.7473 |
| 0.4549 | 35.0 | 5460 | 0.6151 | 0.7473 |
| 0.4277 | 36.0 | 5616 | 0.6209 | 0.7184 |
| 0.4277 | 37.0 | 5772 | 0.6833 | 0.7365 |
| 0.4277 | 38.0 | 5928 | 0.5973 | 0.7220 |
| 0.4108 | 39.0 | 6084 | 0.5932 | 0.7581 |
| 0.4108 | 40.0 | 6240 | 0.4805 | 0.7437 |
| 0.4108 | 41.0 | 6396 | 0.5420 | 0.7401 |
| 0.3987 | 42.0 | 6552 | 0.5820 | 0.7617 |
| 0.3987 | 43.0 | 6708 | 0.5805 | 0.7292 |
| 0.3987 | 44.0 | 6864 | 0.6143 | 0.7473 |
| 0.3785 | 45.0 | 7020 | 0.5329 | 0.7292 |
| 0.3785 | 46.0 | 7176 | 0.7527 | 0.7329 |
| 0.3785 | 47.0 | 7332 | 0.7544 | 0.7256 |
| 0.3785 | 48.0 | 7488 | 0.6422 | 0.7292 |
| 0.3435 | 49.0 | 7644 | 0.7194 | 0.7401 |
| 0.3435 | 50.0 | 7800 | 0.5689 | 0.7401 |
| 0.3435 | 51.0 | 7956 | 0.5635 | 0.7329 |
| 0.3287 | 52.0 | 8112 | 0.6496 | 0.7473 |
| 0.3287 | 53.0 | 8268 | 0.6724 | 0.7220 |
| 0.3287 | 54.0 | 8424 | 0.7439 | 0.7220 |
| 0.3222 | 55.0 | 8580 | 0.5962 | 0.7365 |
| 0.3222 | 56.0 | 8736 | 0.5646 | 0.7437 |
| 0.3222 | 57.0 | 8892 | 0.6753 | 0.7401 |
| 0.2983 | 58.0 | 9048 | 0.5726 | 0.7401 |
| 0.2983 | 59.0 | 9204 | 0.7394 | 0.7256 |
| 0.2983 | 60.0 | 9360 | 0.5553 | 0.7473 |
| 0.2927 | 61.0 | 9516 | 0.6227 | 0.7256 |
| 0.2927 | 62.0 | 9672 | 0.6228 | 0.7365 |
| 0.2927 | 63.0 | 9828 | 0.7299 | 0.7365 |
| 0.2927 | 64.0 | 9984 | 0.6317 | 0.7329 |
| 0.2846 | 65.0 | 10140 | 0.5696 | 0.7401 |
| 0.2846 | 66.0 | 10296 | 0.6101 | 0.7509 |
| 0.2846 | 67.0 | 10452 | 0.5972 | 0.7437 |
| 0.266 | 68.0 | 10608 | 0.5472 | 0.7401 |
| 0.266 | 69.0 | 10764 | 0.6013 | 0.7437 |
| 0.266 | 70.0 | 10920 | 0.6242 | 0.7256 |
| 0.257 | 71.0 | 11076 | 0.5784 | 0.7509 |
| 0.257 | 72.0 | 11232 | 0.6293 | 0.7581 |
| 0.257 | 73.0 | 11388 | 0.6099 | 0.7509 |
| 0.2453 | 74.0 | 11544 | 0.6221 | 0.7401 |
| 0.2453 | 75.0 | 11700 | 0.6113 | 0.7437 |
| 0.2453 | 76.0 | 11856 | 0.5898 | 0.7401 |
| 0.2477 | 77.0 | 12012 | 0.5996 | 0.7545 |
| 0.2477 | 78.0 | 12168 | 0.6357 | 0.7509 |
| 0.2477 | 79.0 | 12324 | 0.5859 | 0.7509 |
| 0.2477 | 80.0 | 12480 | 0.5934 | 0.7545 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
