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| base_model: ProTrekHub/Protein_Encoder_35M |
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| library_name: peft |
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| # Model Card for Model-targetP-ProTrek-35M |
| ## Base model |
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| [ProTrekHub/Protein_Encoder_35M](https://huggingface.co/ProTrekHub/Protein_Encoder_35M) |
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| ## Task description |
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| Detecting Sequence Signals in Targeting Peptides.It is a protein level classification task specificly sub cellular location prediction. |
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| ## Label meaning |
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| noTP 0, SP 1, mTP 2, cTP 3, luTP 4 |
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| ## Citation |
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| Please consider citing the following work if you find the model useful: |
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| https://github.com/JJAlmagro/TargetP-2.0 |
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| ## Task type |
| Protein-level Classification |
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| ## Model input type |
| AA Sequence |
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| ## LoRA config |
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| - **r:** 8 |
| - **lora_dropout:** 0.0 |
| - **lora_alpha:** 16 |
| - **target_modules:** ['intermediate.dense', 'query', 'output.dense', 'key', 'value'] |
| - **modules_to_save:** ['classifier'] |
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| ## Training config |
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| - **optimizer:** |
| - **class:** AdamW |
| - **betas:** (0.9, 0.98) |
| - **weight_decay:** 0.01 |
| - **learning rate:** 0.0005 |
| - **epoch:** 3 |
| - **batch size:** 32 |
| - **precision:** 16-mixed |
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