Model Card for Model-targetP-ProTrek-35M
Base model
ProTrekHub/Protein_Encoder_35M
Task description
Detecting Sequence Signals in Targeting Peptides.It is a protein level classification task specificly sub cellular location prediction.
Label meaning
noTP 0, SP 1, mTP 2, cTP 3, luTP 4
Citation
Please consider citing the following work if you find the model useful:
https://github.com/JJAlmagro/TargetP-2.0
Task type
Protein-level Classification
Model input type
AA Sequence
LoRA config
- r: 8
- lora_dropout: 0.0
- lora_alpha: 16
- target_modules: ['intermediate.dense', 'query', 'output.dense', 'key', 'value']
- modules_to_save: ['classifier']
Training config
- 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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Model tree for YYQ227/TargetP
Base model
ProTrekHub/Protein_Encoder_35M
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("ProTrekHub/Protein_Encoder_35M") model = PeftModel.from_pretrained(base_model, "YYQ227/TargetP")