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sofia-todeschini/
PubMedBERT-LitCovid-v1.3h

Name: PubMedBERT-LitCovid-v1.3h
Availability: InStock

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PubMedBERT-LitCovid-v1.3h

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract on an unknown 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	Hamming loss	F1 micro	F1 macro	F1 weighted	F1 samples	Precision micro	Precision macro	Precision weighted	Precision samples	Recall micro	Recall macro	Recall weighted	Recall samples	Roc Auc	Accuracy
1.2354	1.0	2272	0.4702	0.0473	0.6733	0.2437	0.8136	0.7898	0.5349	0.1961	0.7600	0.7551	0.9084	0.7924	0.9084	0.9263	0.9318	0.5030
0.9475	2.0	4544	0.5277	0.0214	0.8208	0.3449	0.8664	0.8541	0.7441	0.2778	0.8345	0.8362	0.9151	0.7371	0.9151	0.9304	0.9487	0.6209
0.7806	3.0	6816	0.5645	0.0187	0.8432	0.3871	0.8765	0.8632	0.7670	0.3096	0.8337	0.8350	0.9362	0.7431	0.9362	0.9472	0.9601	0.6337
0.5358	4.0	9088	0.7518	0.0145	0.8738	0.4462	0.8893	0.8873	0.8211	0.3653	0.8537	0.8742	0.9337	0.6984	0.9337	0.9443	0.9611	0.7024
0.1808	5.0	11360	0.8774	0.0137	0.8798	0.4661	0.8928	0.8920	0.8303	0.3861	0.8575	0.8800	0.9356	0.7033	0.9356	0.9451	0.9624	0.7154