20230824043537
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: 0.3141
- Accuracy: 0.7401
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: 0.003
- train_batch_size: 4
- 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 |
---|---|---|---|---|
0.7925 | 1.0 | 623 | 0.8673 | 0.4729 |
0.6122 | 2.0 | 1246 | 0.4006 | 0.5415 |
0.5656 | 3.0 | 1869 | 1.2100 | 0.4729 |
0.5981 | 4.0 | 2492 | 0.4232 | 0.5632 |
0.5284 | 5.0 | 3115 | 0.6388 | 0.5523 |
0.6128 | 6.0 | 3738 | 0.4463 | 0.5307 |
0.4769 | 7.0 | 4361 | 0.4020 | 0.6065 |
0.4415 | 8.0 | 4984 | 0.3773 | 0.6029 |
0.4284 | 9.0 | 5607 | 0.3718 | 0.6679 |
0.3893 | 10.0 | 6230 | 0.3479 | 0.6606 |
0.3707 | 11.0 | 6853 | 0.3415 | 0.6751 |
0.3845 | 12.0 | 7476 | 0.3645 | 0.6787 |
0.3667 | 13.0 | 8099 | 0.3591 | 0.6895 |
0.3674 | 14.0 | 8722 | 0.3526 | 0.6931 |
0.3561 | 15.0 | 9345 | 0.3187 | 0.7292 |
0.342 | 16.0 | 9968 | 0.3318 | 0.7004 |
0.3305 | 17.0 | 10591 | 0.3185 | 0.7004 |
0.3269 | 18.0 | 11214 | 0.3733 | 0.6534 |
0.3341 | 19.0 | 11837 | 0.3197 | 0.7040 |
0.3214 | 20.0 | 12460 | 0.3166 | 0.7148 |
0.3109 | 21.0 | 13083 | 0.3257 | 0.7148 |
0.3125 | 22.0 | 13706 | 0.3299 | 0.7292 |
0.3097 | 23.0 | 14329 | 0.4120 | 0.6895 |
0.2918 | 24.0 | 14952 | 0.3158 | 0.7148 |
0.2792 | 25.0 | 15575 | 0.3077 | 0.7256 |
0.2766 | 26.0 | 16198 | 0.3078 | 0.7292 |
0.2811 | 27.0 | 16821 | 0.3033 | 0.7256 |
0.2719 | 28.0 | 17444 | 0.3017 | 0.7148 |
0.2661 | 29.0 | 18067 | 0.2947 | 0.7184 |
0.263 | 30.0 | 18690 | 0.3416 | 0.7329 |
0.2633 | 31.0 | 19313 | 0.3170 | 0.7256 |
0.2517 | 32.0 | 19936 | 0.3063 | 0.7220 |
0.2486 | 33.0 | 20559 | 0.3137 | 0.7256 |
0.252 | 34.0 | 21182 | 0.3118 | 0.7256 |
0.2396 | 35.0 | 21805 | 0.2980 | 0.7220 |
0.2471 | 36.0 | 22428 | 0.3050 | 0.7329 |
0.2361 | 37.0 | 23051 | 0.3366 | 0.7220 |
0.2358 | 38.0 | 23674 | 0.3080 | 0.7473 |
0.2231 | 39.0 | 24297 | 0.3191 | 0.7437 |
0.2298 | 40.0 | 24920 | 0.3018 | 0.7148 |
0.2241 | 41.0 | 25543 | 0.3090 | 0.7401 |
0.2243 | 42.0 | 26166 | 0.3137 | 0.7401 |
0.2237 | 43.0 | 26789 | 0.3277 | 0.7365 |
0.2147 | 44.0 | 27412 | 0.3116 | 0.7437 |
0.2149 | 45.0 | 28035 | 0.3289 | 0.7365 |
0.2087 | 46.0 | 28658 | 0.3241 | 0.7292 |
0.21 | 47.0 | 29281 | 0.3060 | 0.7365 |
0.214 | 48.0 | 29904 | 0.3311 | 0.7329 |
0.2108 | 49.0 | 30527 | 0.3144 | 0.7437 |
0.2029 | 50.0 | 31150 | 0.3094 | 0.7401 |
0.2028 | 51.0 | 31773 | 0.3141 | 0.7473 |
0.2018 | 52.0 | 32396 | 0.3188 | 0.7437 |
0.2079 | 53.0 | 33019 | 0.3138 | 0.7365 |
0.1982 | 54.0 | 33642 | 0.3109 | 0.7401 |
0.1926 | 55.0 | 34265 | 0.3118 | 0.7437 |
0.1972 | 56.0 | 34888 | 0.3270 | 0.7401 |
0.1986 | 57.0 | 35511 | 0.3098 | 0.7365 |
0.1928 | 58.0 | 36134 | 0.3131 | 0.7401 |
0.1974 | 59.0 | 36757 | 0.3132 | 0.7401 |
0.1927 | 60.0 | 37380 | 0.3141 | 0.7401 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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