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| | --- |
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| | base_model: westlake-repl/SaProt_35M_AF2 |
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| | library_name: peft |
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| | --- |
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| | # Model Card for Model-Subcellular_Localization-35M |
| | This model is used for the Subcellular Localization Classification Task. It takes a protein sequence as input and outputs which of the 10 categories the protein belongs to. |
| | |
| | ## Task type |
| | Protein-level Classification |
| | |
| | ## Model input type |
| | SA Sequence |
| | |
| | ## Label meanings |
| | |
| | 0: Nucleus |
| | |
| | 1: Cytoplasm |
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| | 2: Extracellular |
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| | 3: Mitochondrion |
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| | 4: Cell.membrane |
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| | 5: Endoplasmic.reticulum |
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| | 6: Plastid |
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| | 7: Golgi.apparatus |
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| | 8: Lysosome/Vacuole |
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| | 9: Peroxisome |
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| | |
| | ## LoRA config |
| | |
| | - **r:** 8 |
| | - **lora_dropout:** 0.0 |
| | - **lora_alpha:** 16 |
| | - **target_modules:** ['query', 'intermediate.dense', 'key', 'value', 'output.dense'] |
| | - **modules_to_save:** ['classifier'] |
| | |
| | ## Training config |
| | |
| | - **optimizer:** |
| | - **class:** AdamW |
| | - **betas:** (0.9, 0.98) |
| | - **weight_decay:** 0.01 |
| | - **learning rate:** 0.001 |
| | - **epoch:** 1 |
| | - **batch size:** 2 |
| | - **precision:** 16-mixed |
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