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Sam2 Micromat Demo

This model is a fine-tuned version of facebook/sam2.1-hiera-small on the merve/MicroMat-mini dataset.

KindOtherBase modelfacebook/sam2.1-hiera-smallVersionRevision cc19cce

Model source

Kind
Other
File size
147 MB
Base model
facebook/sam2.1-hiera-small
Version
vRevision cc19cce
Updated
Sep 27, 2026
Downloads
12
Tasks
Image segmentation
Source
Hugging Face

Source excerpt

This model is a fine-tuned version of facebook/sam2.1-hiera-small on the merve/MicroMat-mini dataset.

Sources

1 source
Hugging FacePrimaryVersion cc19cceb396c3170458dda5050121f169b05d3e0
huggingface.co/evalstate/sam2-micromat-demo/tree/cc19cceb396c3170458dda5050121f169b05d3e0

Verified Sep 27

Model artifacts

1 artifact

model.safetensors

safetensors · 147 MB · SHA-256 90844ade912a…0159 · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apache-2.0 base_model: facebook/sam2.1-hiera-small tags: - image-segmentation - vision - sam - trackio - trackio:https://huggingface.co/spaces/evalstate/trackio - generated_from_trainer model-index: - name: sam2-micromat-demo 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. --> <a href="https://huggingface.co/spaces/evalstate/trackio" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a> # sam2-micromat-demo This model is a fine-tuned version of [facebook/sam2.1-hiera-small](https://huggingface.co/facebook/sam2.1-hiera-small) on the merve/MicroMat-mini dataset. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - 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: 3.0 ### Training results ### Framework versions - Transformers 5.3.0 - Pytorch 2.10.0+cu128 - Datasets 4.7.0 - Tokenizers 0.22.2

Source context: 12 downloads · 0 likes · Pipeline image-segmentation · Library transformers · Repo evalstate/sam2-micromat-demo