generated_from_trainer

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20230824164051

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:

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:

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 156 0.6969 0.5307
No log 2.0 312 1.5361 0.4693
No log 3.0 468 0.6771 0.5235
0.9695 4.0 624 0.6518 0.5776
0.9695 5.0 780 0.6275 0.5921
0.9695 6.0 936 0.6502 0.5668
0.8132 7.0 1092 0.8188 0.6137
0.8132 8.0 1248 0.6405 0.6570
0.8132 9.0 1404 0.5421 0.7076
0.7231 10.0 1560 0.7011 0.6751
0.7231 11.0 1716 0.6935 0.5993
0.7231 12.0 1872 0.5169 0.7365
0.6369 13.0 2028 0.5523 0.7329
0.6369 14.0 2184 0.5481 0.7292
0.6369 15.0 2340 0.7431 0.6606
0.6369 16.0 2496 0.6122 0.6787
0.5638 17.0 2652 0.5637 0.6931
0.5638 18.0 2808 0.5423 0.7437
0.5638 19.0 2964 0.5347 0.7401
0.5228 20.0 3120 1.6782 0.6354
0.5228 21.0 3276 0.7799 0.6715
0.5228 22.0 3432 0.6873 0.7581
0.4829 23.0 3588 0.6712 0.7329
0.4829 24.0 3744 0.7390 0.7329
0.4829 25.0 3900 0.6802 0.7509
0.4251 26.0 4056 0.5530 0.7076
0.4251 27.0 4212 0.6421 0.7112
0.4251 28.0 4368 0.9956 0.6859
0.395 29.0 4524 0.6741 0.7545
0.395 30.0 4680 0.8871 0.7437
0.395 31.0 4836 0.9265 0.7040
0.395 32.0 4992 0.7189 0.7401
0.3336 33.0 5148 1.1324 0.7040
0.3336 34.0 5304 0.8782 0.7437
0.3336 35.0 5460 0.7878 0.7329
0.3015 36.0 5616 1.1890 0.7040
0.3015 37.0 5772 1.2719 0.7112
0.3015 38.0 5928 1.3208 0.6931
0.2669 39.0 6084 0.9818 0.7437
0.2669 40.0 6240 0.8321 0.7292
0.2669 41.0 6396 0.8419 0.7292
0.2429 42.0 6552 0.9276 0.7365
0.2429 43.0 6708 0.9748 0.7401
0.2429 44.0 6864 0.8934 0.7473
0.2131 45.0 7020 0.9008 0.7473
0.2131 46.0 7176 1.0459 0.7437
0.2131 47.0 7332 1.0222 0.7256
0.2131 48.0 7488 0.9317 0.7545
0.1962 49.0 7644 0.8401 0.7473
0.1962 50.0 7800 0.9513 0.7401
0.1962 51.0 7956 0.9327 0.7401
0.1794 52.0 8112 1.0218 0.7509
0.1794 53.0 8268 1.1332 0.7473
0.1794 54.0 8424 0.8851 0.7365
0.1566 55.0 8580 0.8323 0.7473
0.1566 56.0 8736 0.8375 0.7437
0.1566 57.0 8892 0.8490 0.7509
0.15 58.0 9048 0.9740 0.7509
0.15 59.0 9204 1.1271 0.7473
0.15 60.0 9360 1.1190 0.7437
0.1377 61.0 9516 1.0394 0.7509
0.1377 62.0 9672 0.9735 0.7509
0.1377 63.0 9828 0.9987 0.7437
0.1377 64.0 9984 0.9496 0.7473
0.1283 65.0 10140 1.0721 0.7365
0.1283 66.0 10296 0.8997 0.7617
0.1283 67.0 10452 1.0014 0.7581
0.1212 68.0 10608 1.0382 0.7509
0.1212 69.0 10764 0.9417 0.7437
0.1212 70.0 10920 0.9328 0.7437
0.1101 71.0 11076 0.9084 0.7509
0.1101 72.0 11232 0.9051 0.7545
0.1101 73.0 11388 0.8080 0.7581
0.1147 74.0 11544 0.9505 0.7437
0.1147 75.0 11700 0.8757 0.7437
0.1147 76.0 11856 0.9067 0.7509
0.1095 77.0 12012 0.8988 0.7473
0.1095 78.0 12168 0.8956 0.7473
0.1095 79.0 12324 0.8622 0.7473
0.1095 80.0 12480 0.8794 0.7437

Framework versions