generated_from_trainer

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bert-base-uncased-finetuned-math_punctuation-25-01-two_linear_layers-frozen_bert

This model is a fine-tuned version of on the None 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 Micro f1 Macro f1 Weighted f1
0.193 0.62 500 0.2146 0.8937 0.2360 0.8435
0.1936 1.23 1000 0.2130 0.8937 0.2360 0.8435
0.1924 1.85 1500 0.2119 0.8937 0.2361 0.8435
0.1911 2.47 2000 0.2128 0.8936 0.2369 0.8437
0.1909 3.09 2500 0.2114 0.8937 0.2369 0.8437
0.1904 3.7 3000 0.2137 0.8935 0.2407 0.8445
0.1935 4.32 3500 0.2138 0.8934 0.2469 0.8458
0.1874 4.94 4000 0.2118 0.8929 0.2561 0.8479
0.1908 5.56 4500 0.2134 0.8925 0.2588 0.8483
0.1877 6.17 5000 0.2135 0.8918 0.2628 0.8490
0.1881 6.79 5500 0.2133 0.8931 0.2554 0.8478
0.1902 7.41 6000 0.2137 0.8922 0.2603 0.8485
0.1883 8.02 6500 0.2155 0.8914 0.2655 0.8493
0.19 8.64 7000 0.2154 0.8914 0.2647 0.8490
0.1881 9.26 7500 0.2149 0.8915 0.2645 0.8492
0.1876 9.88 8000 0.2141 0.8911 0.2671 0.8496
0.1879 10.49 8500 0.2155 0.8897 0.2722 0.8501
0.1897 11.11 9000 0.2156 0.8910 0.2670 0.8494
0.1883 11.73 9500 0.2150 0.8910 0.2672 0.8495

Framework versions