Protein fitness regression on avGFP low-N setting (192 train, 48 val)
0.596Spearman CorrelationMutaPLM
Evaluation Results
| Method | Links | |
|---|---|---|
| MutaPLMtraining_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.596 | |
| Tranception_Ltraining_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.594 | |
| ConFittraining_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.564 | |
| ESM-2training_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.554 | |
| Augmented EVmutationtraining_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.512 | |
| Augmented ESMtraining_setting=low-N (192 training / 48 validation samples), head=2-layer MLP, backbone=frozen, epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.497 | |
| Ridge Regressiontraining_setting=low-N (192 training / 48 validation samples), epochs=50, batch_size=16, learning_rate=0.001, loss=MSE2024.10 | 0.298 |