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segformer-ore-minerals-v1
fateme1380/segformer-ore-minerals-v1
segformer-ore-minerals-v1 is a machine learning model from fateme1380. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Nov 19, 2025
- Updated
- Nov 19, 2025
- SHA
- 6af7b373
Base models
Model card
From the Hugging Face model README
<!-- 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-ore-minerals-v1
This model is a fine-tuned version of nvidia/segformer-b0-finetuned-ade-512-512 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3128
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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 12
- 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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4449 | 1.0 | 36 | 1.2149 |
| 0.9787 | 2.0 | 72 | 0.9250 |
| 0.8349 | 3.0 | 108 | 0.7390 |
| 0.6549 | 4.0 | 144 | 0.6332 |
| 0.5758 | 5.0 | 180 | 0.5384 |
| 0.4905 | 6.0 | 216 | 0.4754 |
| 0.4525 | 7.0 | 252 | 0.4232 |
| 0.4037 | 8.0 | 288 | 0.3887 |
| 0.3464 | 9.0 | 324 | 0.3776 |
| 0.3394 | 10.0 | 360 | 0.3582 |
| 0.3105 | 11.0 | 396 | 0.3278 |
| 0.2821 | 12.0 | 432 | 0.3397 |
| 0.2691 | 13.0 | 468 | 0.3194 |
| 0.2642 | 14.0 | 504 | 0.3303 |
| 0.2784 | 15.0 | 540 | 0.3271 |
| 0.2477 | 16.0 | 576 | 0.3144 |
| 0.2472 | 17.0 | 612 | 0.3330 |
| 0.2339 | 18.0 | 648 | 0.3263 |
| 0.2492 | 19.0 | 684 | 0.3235 |
| 0.2226 | 20.0 | 720 | 0.3046 |
| 0.2414 | 21.0 | 756 | 0.3087 |
| 0.2228 | 22.0 | 792 | 0.3016 |
| 0.2023 | 23.0 | 828 | 0.2947 |
| 0.1925 | 24.0 | 864 | 0.3021 |
| 0.2405 | 25.0 | 900 | 0.3051 |
| 0.2327 | 26.0 | 936 | 0.3307 |
| 0.2014 | 27.0 | 972 | 0.2994 |
| 0.2169 | 28.0 | 1008 | 0.3049 |
| 0.1995 | 29.0 | 1044 | 0.3144 |
| 0.2151 | 30.0 | 1080 | 0.3128 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
- Library
- transformers
- Type
- segformer
- License
- other
- Created
- Nov 19, 2025
- Updated
- Nov 19, 2025