This model is a fine-tuned version of facebook/sam2.1-hiera-large on the merve/MicroMat-mini dataset.
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This model is a fine-tuned version of facebook/sam2.1-hiera-large on the merve/MicroMat-mini dataset.
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1 fuenteVerificado 27 sept
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2 extractos--- library_name: transformers license: apache-2.0 base_model: facebook/sam2.1-hiera-large tags: - image-segmentation - vision - sam - trackio - trackio:https://huggingface.co/spaces/merve/trackio - generated_from_trainer model-index: - name: sam2-large-micromat 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/merve/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-large-micromat This model is a fine-tuned version of [facebook/sam2.1-hiera-large](https://huggingface.co/facebook/sam2.1-hiera-large) 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: 10.0 ### Training results ### Framework versions - Transformers 5.3.0 - Pytorch 2.10.0+cu128 - Datasets 4.6.1 - Tokenizers 0.22.2
Source context: 18 downloads · 1 likes · Pipeline image-segmentation · Library transformers · Repo merve/sam2-large-micromat