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

Name: bert-base-uncased-finetuned-math_punctuation-25-01-two_linear_layers-frozen_bert
Availability: InStock

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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:

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The following hyperparameters were used during training:

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