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Segformer B0 Mars Testbed 4class

This model is a fine-tuned version of nvidia/mit-b0 on the Tani04/marstestbedterrain dataset. It achieves the following results on the evaluation set: Loss: 0.6859 Mean Iou: 0.2495 Mean Accuracy: 0.9980 Overall...

Sourcehuggingface.co/Tani04/segformer-b0-mars-testbed-4class/tree/5e585918e26b1b4f67550bdd23cc3e914de151d7
TypeOtherModèle de basenvidia/mit-b0VersionRevision 5e58591CClasse

Source du modèle

Type
Other
Taille du fichier
14,2 MB
Modèle de base
nvidia/mit-b0
Version
vRevision 5e58591
Mis à jour
16 sept. 2026
Téléchargements
3
Source
Hugging Face

Description de la source

segformer-b0-mars-testbed-4class

This model is a fine-tuned version of nvidia/mit-b0 on the Tani04/mars_testbed_terrain dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6859
  • Mean Iou: 0.2495
  • Mean Accuracy: 0.9980
  • Overall Accuracy: 0.9980
  • Accuracy Flat Bedrock: 0.9980
  • Accuracy Flat Gravel: nan
  • Accuracy Hard Gravel: nan
  • Accuracy Obstacle: nan
  • Iou Flat Bedrock: 0.9980
  • Iou Flat Gravel: 0.0
  • Iou Hard Gravel: 0.0
  • Iou Obstacle: 0.0

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: 6e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training LossEpochStepValidation LossMean IouMean AccuracyOverall AccuracyAccuracy Flat BedrockAccuracy Flat GravelAccuracy Hard GravelAccuracy ObstacleIou Flat BedrockIou Flat GravelIou Hard GravelIou Obstacle
1.20072.5201.28850.21310.85240.85240.8524nannannan0.85240.00.00.0
1.01655.0400.95040.24660.98630.98630.9863nannannan0.98630.00.00.0
0.88327.5600.77210.24730.98900.98900.9890nannannan0.98900.00.00.0
0.776510.0800.72400.24880.99500.99500.9950nannannan0.99500.00.00.0
0.769312.51000.69200.24890.99570.99570.9957nannannan0.99570.00.00.0
0.701115.01200.68590.24950.99800.99800.9980nannannan0.99800.00.00.0

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.4.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3

Sources

1 source
Hugging FacePrincipalVersion 5e585918e26b1b4f67550bdd23cc3e914de151d7
huggingface.co/Tani04/segformer-b0-mars-testbed-4class/tree/5e585918e26b1b4f67550bdd23cc3e914de151d7

Vérifié 1 sept.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 14,2 MB · SHA-256 b3eb42bf94bd…c0cd · Hugging Face

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Extraits de sources

2 extraits
Readme1 sept.huggingface.co/Tani04/segformer-b0-mars-testbed-4class

--- library_name: transformers license: other base_model: nvidia/mit-b0 tags: - vision - image-segmentation - mars-terrain - generated_from_trainer model-index: - name: segformer-b0-mars-testbed-4class 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. --> # segformer-b0-mars-testbed-4class This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the Tani04/mars_testbed_terrain dataset. It achieves the following results on the evaluation set: - Loss: 0.6859 - Mean Iou: 0.2495 - Mean Accuracy: 0.9980 - Overall Accuracy: 0.9980 - Accuracy Flat Bedrock: 0.9980 - Accuracy Flat Gravel: nan - Accuracy Hard Gravel: nan - Accuracy Obstacle: nan - Iou Flat Bedrock: 0.9980 - Iou Flat Gravel: 0.0 - Iou Hard Gravel: 0.0 - Iou Obstacle: 0.0 ## 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: 6e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 15 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Flat Bedrock | Accuracy Flat Gravel | Accuracy Hard Gravel | Accuracy Obstacle | Iou Flat Bedrock | Iou Flat Gravel | Iou Hard Gravel | Iou Obstacle | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------------:|:--------------------:|:--------------------:|:-----------------:|:----------------:|:---------------:|:---------------:|:------------:| | 1.2007 | 2.5 | 20 | 1.2885 | 0.2131 | 0.8524 | 0.8524 | 0.8524 | nan | nan | nan | 0.8524 | 0.0 | 0.0 | 0.0 | | 1.0165 | 5.0 | 40 | 0.9504 | 0.2466 | 0.9863 | 0.9863 | 0.9863 | nan | nan | nan | 0.9863 | 0.0 | 0.0 | 0.0 | | 0.8832 | 7.5 | 60 | 0.7721 | 0.2473 | 0.9890 | 0.9890 | 0.9890 | nan | nan | nan | 0.9890 | 0.0 | 0.0 | 0.0 | | 0.7765 | 10.0 | 80 | 0.7240 | 0.2488 | 0.9950 | 0.9950 | 0.9950 | nan | nan...

Note1 sept.huggingface.co/Tani04/segformer-b0-mars-testbed-4class

Source context: 3 downloads · 0 likes · Pipeline image-segmentation · Library transformers · Repo Tani04/segformer-b0-mars-testbed-4class