Research map / Architectures and efficiency / RNNs and normalization
DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add residual layers to enable a deeper word representation network | DeepVar on tmVar · tmVar test | F1: 90.42 -> 90.78 | Helped |
| Use BiLSTM instead of CNN for character representation (ablation) | DeepVar · tmVar test | F1: 90.58 -> 90.78 | Helped |
| Replace BioW2V with BioELMO (ablation) | DeepVar · tmVar test | F1: 90.78 -> 90.58 | Hurt |
| Replace BioW2V with BioBert (ablation) | DeepVar · tmVar test | F1: 90.78 -> 90.46 | Hurt |
| Replace BioW2V with BioFlair (ablation) | DeepVar · tmVar test | F1: 90.78 -> 90.14 | Hurt |
| Use contextual BioELMO instead of BioW2V (ablation) | DNN · tmVar test | F1: 88.49 -> 90.42 | Helped |
| Use contextual BioBert instead of BioW2V (ablation) | DNN · tmVar test | F1: 88.49 -> 90.41 | Helped |
| Use contextual BioFlair instead of BioW2V (ablation) | DNN · tmVar test | F1: 88.49 -> 90.04 | Helped |
| Use SGD instead of RMSP (ablation) | DeepVar · tmVar test | F1: 90.78 -> 86.65 | Hurt |
| Use ADAM instead of RMSP (ablation) | DeepVar · tmVar test | F1: 90.78 -> 90.42 | Hurt |
| Use SGD instead of RMSP (ablation) | DNN · tmVar test | F1: 90.42 -> 82.44 | Hurt |
| Use ADAM instead of RMSP (ablation) | DNN · tmVar test | F1: 90.42 -> 89.60 | Hurt |
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