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20230824210941
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: 0.8686
- Accuracy: 0.7256
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 | 0.8228 | 0.5307 |
| No log | 2.0 | 312 | 0.7014 | 0.5271 |
| No log | 3.0 | 468 | 0.9320 | 0.4657 |
| 0.9247 | 4.0 | 624 | 0.8551 | 0.5307 |
| 0.9247 | 5.0 | 780 | 0.8862 | 0.5235 |
| 0.9247 | 6.0 | 936 | 0.6306 | 0.6282 |
| 0.8754 | 7.0 | 1092 | 0.9270 | 0.5957 |
| 0.8754 | 8.0 | 1248 | 0.6627 | 0.6354 |
| 0.8754 | 9.0 | 1404 | 0.7200 | 0.6137 |
| 0.745 | 10.0 | 1560 | 0.5993 | 0.6751 |
| 0.745 | 11.0 | 1716 | 0.7300 | 0.6318 |
| 0.745 | 12.0 | 1872 | 0.7463 | 0.6823 |
| 0.6869 | 13.0 | 2028 | 0.8378 | 0.6029 |
| 0.6869 | 14.0 | 2184 | 0.6182 | 0.7076 |
| 0.6869 | 15.0 | 2340 | 0.9895 | 0.6209 |
| 0.6869 | 16.0 | 2496 | 0.7414 | 0.6859 |
| 0.6526 | 17.0 | 2652 | 0.6260 | 0.6931 |
| 0.6526 | 18.0 | 2808 | 0.5832 | 0.7365 |
| 0.6526 | 19.0 | 2964 | 0.6509 | 0.6968 |
| 0.5884 | 20.0 | 3120 | 0.7808 | 0.6751 |
| 0.5884 | 21.0 | 3276 | 0.6212 | 0.7437 |
| 0.5884 | 22.0 | 3432 | 0.8835 | 0.6354 |
| 0.5748 | 23.0 | 3588 | 0.8832 | 0.6570 |
| 0.5748 | 24.0 | 3744 | 0.8348 | 0.6679 |
| 0.5748 | 25.0 | 3900 | 0.8357 | 0.6859 |
| 0.5519 | 26.0 | 4056 | 0.5958 | 0.7256 |
| 0.5519 | 27.0 | 4212 | 0.5952 | 0.7365 |
| 0.5519 | 28.0 | 4368 | 0.6118 | 0.7256 |
| 0.5239 | 29.0 | 4524 | 0.8448 | 0.6823 |
| 0.5239 | 30.0 | 4680 | 0.6541 | 0.7112 |
| 0.5239 | 31.0 | 4836 | 0.9677 | 0.6390 |
| 0.5239 | 32.0 | 4992 | 0.7328 | 0.7076 |
| 0.4732 | 33.0 | 5148 | 0.8215 | 0.6643 |
| 0.4732 | 34.0 | 5304 | 0.7120 | 0.7112 |
| 0.4732 | 35.0 | 5460 | 0.7292 | 0.7437 |
| 0.4314 | 36.0 | 5616 | 0.7357 | 0.7220 |
| 0.4314 | 37.0 | 5772 | 1.0189 | 0.6606 |
| 0.4314 | 38.0 | 5928 | 0.7766 | 0.6787 |
| 0.4113 | 39.0 | 6084 | 0.9918 | 0.6679 |
| 0.4113 | 40.0 | 6240 | 0.8170 | 0.7329 |
| 0.4113 | 41.0 | 6396 | 0.7732 | 0.7184 |
| 0.3872 | 42.0 | 6552 | 0.7271 | 0.7653 |
| 0.3872 | 43.0 | 6708 | 0.8372 | 0.7365 |
| 0.3872 | 44.0 | 6864 | 0.8637 | 0.7148 |
| 0.3747 | 45.0 | 7020 | 0.8895 | 0.7220 |
| 0.3747 | 46.0 | 7176 | 1.3025 | 0.6931 |
| 0.3747 | 47.0 | 7332 | 0.8508 | 0.7437 |
| 0.3747 | 48.0 | 7488 | 0.9201 | 0.7220 |
| 0.3401 | 49.0 | 7644 | 1.0286 | 0.7184 |
| 0.3401 | 50.0 | 7800 | 0.8711 | 0.7365 |
| 0.3401 | 51.0 | 7956 | 1.0386 | 0.7256 |
| 0.3162 | 52.0 | 8112 | 0.8634 | 0.7401 |
| 0.3162 | 53.0 | 8268 | 0.9121 | 0.7184 |
| 0.3162 | 54.0 | 8424 | 0.8510 | 0.7292 |
| 0.3146 | 55.0 | 8580 | 0.8323 | 0.7329 |
| 0.3146 | 56.0 | 8736 | 1.1691 | 0.6968 |
| 0.3146 | 57.0 | 8892 | 0.9995 | 0.7292 |
| 0.3049 | 58.0 | 9048 | 0.8166 | 0.7184 |
| 0.3049 | 59.0 | 9204 | 1.0304 | 0.7184 |
| 0.3049 | 60.0 | 9360 | 0.8338 | 0.7184 |
| 0.2932 | 61.0 | 9516 | 0.8818 | 0.7220 |
| 0.2932 | 62.0 | 9672 | 1.0405 | 0.7184 |
| 0.2932 | 63.0 | 9828 | 0.9091 | 0.7112 |
| 0.2932 | 64.0 | 9984 | 0.9134 | 0.7256 |
| 0.2786 | 65.0 | 10140 | 0.8553 | 0.7329 |
| 0.2786 | 66.0 | 10296 | 0.9198 | 0.7365 |
| 0.2786 | 67.0 | 10452 | 0.8613 | 0.7329 |
| 0.2616 | 68.0 | 10608 | 0.8299 | 0.7292 |
| 0.2616 | 69.0 | 10764 | 0.9801 | 0.7148 |
| 0.2616 | 70.0 | 10920 | 0.8634 | 0.7256 |
| 0.2573 | 71.0 | 11076 | 0.8447 | 0.7509 |
| 0.2573 | 72.0 | 11232 | 0.8127 | 0.7437 |
| 0.2573 | 73.0 | 11388 | 0.8869 | 0.7256 |
| 0.248 | 74.0 | 11544 | 0.8170 | 0.7256 |
| 0.248 | 75.0 | 11700 | 0.9370 | 0.7220 |
| 0.248 | 76.0 | 11856 | 0.8273 | 0.7220 |
| 0.2513 | 77.0 | 12012 | 0.8745 | 0.7220 |
| 0.2513 | 78.0 | 12168 | 0.8785 | 0.7292 |
| 0.2513 | 79.0 | 12324 | 0.8585 | 0.7256 |
| 0.2513 | 80.0 | 12480 | 0.8686 | 0.7256 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
