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CellST-v3-Spatial-Transcriptomics

spatial-transcriptomics

celltype-classification

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CellST v3 — Spatial Transcriptomics

Fine-tuned CellFM 80M model for spatial transcriptomics analysis.

Architecture

Encoder: 6 RetentionLayer blocks, 1536 dims, 48 heads (~80M params)
Decoders: ValueDecoder, CellwiseDecoder, CelltypeDecoder
Contrastive head: Spatial contrastive loss with distance-weighted InfoNCE

Training

Base model: CellFM 80M (MindSpore to PyTorch conversion)
Data: Mouse brain spatial transcriptomics (4 section splits, 215 training files)
Hardware: 8x AMD MI325X GPUs
Precision: bfloat16 (autocast)
Optimizer: AdamW (pretrained LR=1e-4, new heads LR=1e-5)
Epochs: 5

Checkpoints

Epoch	Loss
1	1.2386
2	1.1501
3	1.1283
4	(saved)
5	(in progress)

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