Skip to content Studio Make images and video without living inside the AI toolchain.
A local-first workspace for turning ComfyUI workflows into tools you can use, understand, and reuse.
© 2026 Tea Time Labs
Local AI creation, organized.
Have a ComfyUI workflow? Get a readable Workflow Doc in your browser. Make a workflow readable. Try it now ↗
Mask2former Swin Base Apple Dms Run1 | ST Studio
Resources / Mask2former Swin Base Apple Dms Run1 Mask2former Swin Base Apple Dms Run1 This model is a fine-tuned version of facebook/mask2former-swin-base-ade-semantic on the AllanK24/apple-dms-materials dataset. It achieves the following results on the evaluation set: Mean Iou: 0.0129 Mean Accuracy:...
This model is a fine-tuned version of facebook/mask2former-swin-base-ade-semantic on the AllanK24/apple-dms-materials dataset. It achieves the following results on the evaluation set: Mean Iou: 0.0129 Mean Accuracy:...
Kind Other Base model facebook/mask2former-swin-base-ade-semantic Version Revision a1979ff
Model source
Kind Other
File size 412 MB
Base model facebook/mask2former-swin-base-ade-semantic
Version vRevision a1979ff
Updated Sep 27, 2026
Downloads 5
Tasks Image segmentation
Source Hugging Face
mask2former-swin-base-apple-dms-run1
This model is a fine-tuned version of facebook/mask2former-swin-base-ade-semantic on the AllanK24/apple-dms-materials dataset.
It achieves the following results on the evaluation set:
Model artifacts
1 artifact model.safetensors
safetensors · 412 MB · SHA-256 2c89ff9ac90d…5c69 · Hugging Face
Download Source excerpts
2 excerpts
Mean Iou: 0.0129
Mean Accuracy: 0.0190
Overall Accuracy: 0.2006
Iou Animal Skin: 0.0
Accuracy Animal Skin: 0.0
Iou Bone Teeth Horn: 0.0
Accuracy Bone Teeth Horn: 0.0
Iou Brickwork: 0.0
Accuracy Brickwork: 0.0
Iou Cardboard: 0.0
Accuracy Cardboard: 0.0
Iou Carpet Rug: 0.0000
Accuracy Carpet Rug: 0.0000
Iou Ceiling Tile: 0.0
Accuracy Ceiling Tile: 0.0
Iou Ceramic: 0.0
Accuracy Ceramic: 0.0
Iou Chalkboard Blackboard: 0.0
Accuracy Chalkboard Blackboard: 0.0
Iou Clutter: 0.0
Accuracy Clutter: 0.0
Iou Concrete: 0.0
Accuracy Concrete: 0.0
Iou Cork Corkboard: 0.0
Accuracy Cork Corkboard: 0.0
Iou Engineered Stone: 0.0
Accuracy Engineered Stone: 0.0
Iou Fabric Cloth: 0.0045
Accuracy Fabric Cloth: 0.0045
Iou Fiberglass Wool: 0.0
Accuracy Fiberglass Wool: 0.0
Iou Fire: 0.0
Accuracy Fire: 0.0
Iou Foliage: 0.0
Accuracy Foliage: 0.0
Iou Food: 0.0
Accuracy Food: 0.0
Iou Fur: 0.0
Accuracy Fur: 0.0
Iou Gemstone Quartz: 0.0
Accuracy Gemstone Quartz: 0.0
Iou Glass: 0.0593
Accuracy Glass: 0.0676
Iou Hair: 0.0685
Accuracy Hair: 0.0885
Iou Ice: 0.0
Accuracy Ice: 0.0
Iou Leather: 0.0
Accuracy Leather: 0.0
Iou Liquid Non-water: 0.0
Accuracy Liquid Non-water: 0.0
Iou Metal: 0.0036
Accuracy Metal: 0.0038
Iou Mirror: 0.0
Accuracy Mirror: 0.0
Iou Paint Plaster Enamel: 0.4088
Accuracy Paint Plaster Enamel: 0.6439
Iou Paper: 0.0141
Accuracy Paper: 0.0153
Iou Pearl: 0.0
Accuracy Pearl: 0.0
Iou Photograph Painting: 0.0
Accuracy Photograph Painting: 0.0
Iou Plastic Clear: 0.0
Accuracy Plastic Clear: 0.0
Iou Plastic Non-clear: 0.0000
Accuracy Plastic Non-clear: 0.0000
Iou Rubber Latex: 0.0
Accuracy Rubber Latex: 0.0
Iou Sand: 0.0
Accuracy Sand: 0.0
Iou Skin Lips: 0.1127
Accuracy Skin Lips: 0.1643
Iou Sky: 0.0
Accuracy Sky: 0.0
Iou Snow: 0.0
Accuracy Snow: 0.0
Iou Soap: 0.0
Accuracy Soap: 0.0
Iou Soil Mud: 0.0
Accuracy Soil Mud: 0.0
Iou Sponge: 0.0
Accuracy Sponge: 0.0
Iou Stone Natural: 0.0
Accuracy Stone Natural: 0.0
Iou Stone Polished: 0.0
Accuracy Stone Polished: 0.0
Iou Styrofoam: 0.0
Accuracy Styrofoam: 0.0
Iou Tile: 0.0
Accuracy Tile: 0.0
Iou Wallpaper: 0.0
Accuracy Wallpaper: 0.0
Iou Water: 0.0
Accuracy Water: 0.0
Iou Wax: 0.0
Accuracy Wax: 0.0
Iou Whiteboard: 0.0
Accuracy Whiteboard: 0.0
Iou Wicker: 0.0
Accuracy Wicker: 0.0
Iou Wood: 0.0001
Accuracy Wood: 0.0001
Iou Wood Tree: 0.0
Accuracy Wood Tree: 0.0
Iou Asphalt: 0.0
Accuracy Asphalt: 0.0
Loss: 411.6706
Eval Runtime: 41.6536
Eval Samples Per Second: 28.425
Eval Steps Per Second: 14.212
Model description
Intended uses & limitations
Training and evaluation data
Training procedure
Training hyperparameters The following hyperparameters were used during training:
learning_rate: 0.001
train_batch_size: 32
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 256
total_eval_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results Training Loss Epoch Step Mean Iou Mean Accuracy Overall Accuracy Iou Animal Skin Accuracy Animal Skin Iou Bone Teeth Horn Accuracy Bone Teeth Horn Iou Brickwork Accuracy Brickwork Iou Cardboard Accuracy Cardboard Iou Carpet Rug Accuracy Carpet Rug Iou Ceiling Tile Accuracy Ceiling Tile Iou Ceramic Accuracy Ceramic Iou Chalkboard Blackboard 475.7108 0.5682 50 0.0129 0.0190 0.2006 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
---
library_name: transformers
license: other
base_model: facebook/mask2former-swin-base-ade-semantic
tags:
- vision
- image-segmentation
- mask2former
- material-segmentation
- generated_from_trainer
model-index:
- name: mask2former-swin-base-apple-dms-run1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mask2former-swin-base-apple-dms-run1
This model is a fine-tuned version of [facebook/mask2former-swin-base-ade-semantic](https://huggingface.co/facebook/mask2former-swin-base-ade-semantic) on the AllanK24/apple-dms-materials dataset.
It achieves the following results on the evaluation set:
- Mean Iou: 0.0129
- Mean Accuracy: 0.0190
- Overall Accuracy: 0.2006
- Iou Animal Skin: 0.0
- Accuracy Animal Skin: 0.0
- Iou Bone Teeth Horn: 0.0
- Accuracy Bone Teeth Horn: 0.0
- Iou Brickwork: 0.0
- Accuracy Brickwork: 0.0
- Iou Cardboard: 0.0
- Accuracy Cardboard: 0.0
- Iou Carpet Rug: 0.0000
- Accuracy Carpet Rug: 0.0000
- Iou Ceiling Tile: 0.0
- Accuracy Ceiling Tile: 0.0
- Iou Ceramic: 0.0
- Accuracy Ceramic: 0.0
- Iou Chalkboard Blackboard: 0.0
- Accuracy Chalkboard Blackboard: 0.0
- Iou Clutter: 0.0
- Accuracy Clutter: 0.0
- Iou Concrete: 0.0
- Accuracy Concrete: 0.0
- Iou Cork Corkboard: 0.0
- Accuracy Cork Corkboard: 0.0
- Iou Engineered Stone: 0.0
- Accuracy Engineered Stone: 0.0
- Iou Fabric Cloth: 0.0045
- Accuracy Fabric Cloth: 0.0045
- Iou Fiberglass Wool: 0.0
- Accuracy Fiberglass Wool: 0.0
- Iou Fire: 0.0
- Accuracy Fire: 0.0
- Iou Foliage: 0.0
- Accuracy Foliage: 0.0
- Iou Food: 0.0
- Accuracy Food: 0.0
- Iou Fur: 0.0
- Accuracy Fur: 0.0
- Iou Gemstone Quartz: 0.0
- Accuracy Gemstone Quartz: 0.0
- Iou Glass: 0.0593
- Accuracy Glass: 0.0676
- Iou Hair: 0.0685
- Accuracy Hair: 0.0885
- Iou Ice: 0.0
- Accuracy Ice: 0.0
- Iou Leather: 0.0
- Accuracy Leather: 0.0
- Iou Liquid Non-water: 0.0
- Accuracy Liquid Non-water: 0.0
- Iou Metal: 0.0036
- Accuracy Metal: 0.0038
- Iou Mirror: 0.0
- Accuracy Mirror: 0.0
- Iou Paint Plaster Enamel: 0.4088
- Accuracy Paint Plaster Enamel: 0.6439
- Iou Paper: 0.0141
- Accuracy Paper: 0.0153
- Iou Pearl: 0.0
- Accuracy Pearl: 0.0
- Iou Photograph Painting: 0.0
- Accuracy Photograph Painting: 0.0
- Iou Plastic Clear: 0.0
- Accuracy Plastic Clear: 0.0
- Iou Plastic...
Source context: 5 downloads · 0 likes · Pipeline image-segmentation · Library transformers · Repo AllanK24/mask2former-swin-base-apple-dms-run1
Accuracy Chalkboard Blackboard
Accuracy Engineered Stone
Accuracy Liquid Non-water
Accuracy Paint Plaster Enamel
Accuracy Photograph Painting
Accuracy Plastic Non-clear
475.7108 0.5682 50 0.0129 0.0190 0.2006 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0000 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0045 0.0045 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0593 0.0676 0.0685 0.0885 0.0 0.0 0.0 0.0 0.0 0.0 0.0036 0.0038 0.0 0.0 0.4088 0.6439 0.0141 0.0153 0.0 0.0 0.0 0.0 0.0 0.0 0.0000 0.0000 0.0 0.0 0.0 0.0 0.1127 0.1643 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ...
