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esm2-150m-protein-localization
rustambekurokov/esm2-150m-protein-localization
esm2-150m-protein-localization is a machine learning model from rustambekurokov. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Fine-tuned ESM-2 150M for protein subcellular localization (10 classes). All parameters trained end-to-end. Best accuracy among full fine-tune models.
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Public
Updated Jul 8, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026
- SHA
- 0c0cbc8d
Base models
Datasets
Model card
From the Hugging Face model README
ESM-2 150M — Protein Subcellular Localization (Full Fine-Tune)
Fine-tuned ESM-2 150M for protein subcellular localization (10 classes). All parameters trained end-to-end. Best accuracy among full fine-tune models.
Results
| Metric | Score |
|---|---|
| Accuracy | 76.6% |
| F1 (macro) | 0.696 |
| F1 (weighted) | 0.761 |
| MCC | 0.706 |
Architecture
ESM-2 150M (all trainable) → Mean pooling → LayerNorm → Linear(640→160) → GELU → Linear(160→10)
Training
- Dataset: DeepLoc 2.0 (17,266 train / 3,700 val / 3,701 test)
- Strategy: Full fine-tune (all 150M parameters)
- Epochs: 10
- Learning rate: 1e-5
- Hardware: NVIDIA DGX Spark
All Models in This Project
| Model | Strategy | Accuracy | Link |
|---|---|---|---|
| ESM-2 8M | Linear probe | 69.6% | whiteh4t/esm2-8m-protein-localization |
| ESM-2 35M | Full fine-tune | 74.3% | whiteh4t/esm2-35m-protein-localization |
| ESM-2 150M | Full fine-tune | 76.6% | This repo |
| ESM-2 650M | LoRA (r=16) | 76.5% | whiteh4t/esm2-650m-protein-localization-lora |
Links
- Demo: HuggingFace Space
- Code: GitHub
- License
- mit
- Languages
- en
- Created
- Jul 8, 2026
- Updated
- Jul 8, 2026