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Brizape/
Variome_5e-05_0404_ES6_strict_tok

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Variome_5e-05_0404_ES6_strict_tok

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext 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	Precision	Recall	F1	Accuracy
0.5718	0.13	25	0.1871	0.0	0.0	0.0	0.9759
0.1825	0.26	50	0.1824	0.0	0.0	0.0	0.9759
0.1927	0.39	75	0.1846	0.0	0.0	0.0	0.9759
0.1807	0.52	100	0.1811	0.0	0.0	0.0	0.9759
0.1695	0.65	125	0.1861	0.0	0.0	0.0	0.9759
0.1782	0.79	150	0.1807	0.0	0.0	0.0	0.9759
0.174	0.92	175	0.1798	0.0	0.0	0.0	0.9759
0.1547	1.05	200	0.1706	0.0	0.0	0.0	0.9759
0.1539	1.18	225	0.1402	0.0	0.0	0.0	0.9759
0.1415	1.31	250	0.1281	0.3333	0.0010	0.0019	0.9759
0.125	1.44	275	0.1154	0.1606	0.1104	0.1308	0.9772
0.1143	1.57	300	0.1043	0.2136	0.1689	0.1886	0.9774
0.1009	1.7	325	0.1014	0.2602	0.2207	0.2388	0.9784
0.0952	1.83	350	0.0918	0.3286	0.2418	0.2786	0.9798
0.0754	1.96	375	0.0908	0.5	0.2332	0.3181	0.9804
0.0759	2.09	400	0.0896	0.5473	0.3052	0.3919	0.9823
0.0676	2.23	425	0.0817	0.4222	0.3388	0.3759	0.9820
0.0788	2.36	450	0.0997	0.5549	0.1699	0.2601	0.9793
0.0692	2.49	475	0.0780	0.4634	0.4251	0.4434	0.9828
0.07	2.62	500	0.0734	0.5784	0.4002	0.4731	0.9835
0.0694	2.75	525	0.0693	0.5741	0.4722	0.5182	0.9850
0.0645	2.88	550	0.0677	0.6261	0.4741	0.5396	0.9850
0.0685	3.01	575	0.0698	0.5831	0.4511	0.5087	0.9847
0.0505	3.14	600	0.0683	0.6382	0.5029	0.5625	0.9852