generated_from_trainer

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20230825050330

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 0.6296 0.5235
No log 2.0 312 0.8911 0.4729
No log 3.0 468 0.6506 0.5162
0.9735 4.0 624 0.8420 0.4765
0.9735 5.0 780 0.6867 0.5307
0.9735 6.0 936 0.6089 0.5884
0.8059 7.0 1092 0.5402 0.6209
0.8059 8.0 1248 0.5361 0.6245
0.8059 9.0 1404 0.7656 0.5271
0.7362 10.0 1560 0.4564 0.7148
0.7362 11.0 1716 0.6545 0.6209
0.7362 12.0 1872 0.5022 0.6787
0.6634 13.0 2028 0.4531 0.7148
0.6634 14.0 2184 0.4135 0.7256
0.6634 15.0 2340 0.4077 0.7112
0.6634 16.0 2496 0.4737 0.6823
0.7064 17.0 2652 0.4535 0.7509
0.7064 18.0 2808 0.4382 0.6931
0.7064 19.0 2964 0.3934 0.7184
0.6064 20.0 3120 0.6309 0.6498
0.6064 21.0 3276 0.4171 0.7112
0.6064 22.0 3432 0.4834 0.7076
0.5413 23.0 3588 0.3896 0.7184
0.5413 24.0 3744 0.4087 0.7473
0.5413 25.0 3900 0.4606 0.7004
0.543 26.0 4056 0.4200 0.7184
0.543 27.0 4212 0.3754 0.7365
0.543 28.0 4368 0.4998 0.7112
0.4837 29.0 4524 0.4105 0.7329
0.4837 30.0 4680 0.4650 0.7365
0.4837 31.0 4836 0.5529 0.6895
0.4837 32.0 4992 0.4410 0.7617
0.4667 33.0 5148 0.4656 0.7184
0.4667 34.0 5304 0.4388 0.7256
0.4667 35.0 5460 0.4408 0.7473
0.429 36.0 5616 0.3913 0.7256
0.429 37.0 5772 0.5831 0.7292
0.429 38.0 5928 0.3963 0.7220
0.4242 39.0 6084 0.4154 0.7329
0.4242 40.0 6240 0.6203 0.6931
0.4242 41.0 6396 0.4409 0.7653
0.3911 42.0 6552 0.4201 0.7437
0.3911 43.0 6708 0.4647 0.7329
0.3911 44.0 6864 0.4582 0.7292
0.3749 45.0 7020 0.4134 0.7329
0.3749 46.0 7176 0.4969 0.7292
0.3749 47.0 7332 0.5039 0.7545
0.3749 48.0 7488 0.4449 0.7365
0.3442 49.0 7644 0.4380 0.7365
0.3442 50.0 7800 0.4263 0.7473
0.3442 51.0 7956 0.4364 0.7437
0.3162 52.0 8112 0.4414 0.7617
0.3162 53.0 8268 0.5216 0.7329
0.3162 54.0 8424 0.5045 0.7256
0.3127 55.0 8580 0.3838 0.7509
0.3127 56.0 8736 0.4114 0.7437
0.3127 57.0 8892 0.5307 0.7256
0.3128 58.0 9048 0.4306 0.7509
0.3128 59.0 9204 0.5574 0.7184
0.3128 60.0 9360 0.3862 0.7653
0.2924 61.0 9516 0.4506 0.7329
0.2924 62.0 9672 0.4236 0.7473
0.2924 63.0 9828 0.4497 0.7726
0.2924 64.0 9984 0.4775 0.7437
0.2812 65.0 10140 0.4406 0.7509
0.2812 66.0 10296 0.4474 0.7581
0.2812 67.0 10452 0.4287 0.7545
0.2738 68.0 10608 0.4214 0.7581
0.2738 69.0 10764 0.4300 0.7509
0.2738 70.0 10920 0.4047 0.7581
0.2596 71.0 11076 0.4289 0.7509
0.2596 72.0 11232 0.4178 0.7762
0.2596 73.0 11388 0.4273 0.7581
0.2437 74.0 11544 0.4166 0.7653
0.2437 75.0 11700 0.4299 0.7581
0.2437 76.0 11856 0.3947 0.7545
0.2513 77.0 12012 0.4163 0.7581
0.2513 78.0 12168 0.4200 0.7545
0.2513 79.0 12324 0.4037 0.7617
0.2513 80.0 12480 0.4125 0.7545

Framework versions