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segformer-b0-finetuned-segments-pv

Image Segmentation
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metadata
license: other
base_model: nvidia/segformer-b0-finetuned-ade-512-512
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
metrics:
  - precision
model-index:
  - name: segformer-b0-finetuned-segments-pv
    results: []

Visualize in Weights & Biases

segformer-b0-finetuned-segments-pv

This model is a fine-tuned version of nvidia/segformer-b0-finetuned-ade-512-512 on the mouadenna/satellite_PV_dataset_train_test dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0224
  • Mean Iou: 0.8462
  • Precision: 0.9229

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: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Mean Iou Precision
0.0043 1.0 3666 0.0095 0.7784 0.8863
0.0036 2.0 7332 0.0082 0.8127 0.8991
0.0004 3.0 10998 0.0085 0.7946 0.8844
0.0 4.0 14664 0.0082 0.8313 0.9130
0.0 5.0 18330 0.0089 0.8147 0.9092
0.002 6.0 21996 0.0117 0.8121 0.9275
0.0017 7.0 25662 0.0105 0.7984 0.8629
0.0 8.0 29328 0.0108 0.8169 0.8889
0.0029 9.0 32994 0.0133 0.8224 0.9096
0.006 10.0 36660 0.0106 0.8280 0.8829
0.026 11.0 40326 0.0102 0.8501 0.9210
0.0 12.0 43992 0.0118 0.8339 0.9022
0.0019 13.0 47658 0.0139 0.8360 0.9103
0.0018 14.0 51324 0.0140 0.8332 0.9161
0.0039 15.0 54990 0.0129 0.8297 0.9012
0.0025 16.0 58656 0.0166 0.8368 0.9030
0.0073 17.0 62322 0.0148 0.8334 0.8950
0.0017 18.0 65988 0.0157 0.8451 0.9166
0.0 19.0 69654 0.0184 0.8129 0.9161
0.0013 20.0 73320 0.0162 0.8333 0.9042
0.0014 21.0 76986 0.0167 0.8470 0.9178
0.0015 22.0 80652 0.0147 0.8429 0.9114
0.0015 23.0 84318 0.0149 0.8458 0.8978
0.0009 24.0 87984 0.0158 0.8416 0.9072
0.0014 25.0 91650 0.0144 0.8457 0.9185
0.0013 26.0 95316 0.0164 0.8482 0.9212
0.0043 27.0 98982 0.0162 0.8400 0.9005
0.0024 28.0 102648 0.0203 0.8468 0.9217
0.0 29.0 106314 0.0192 0.8431 0.9142
0.0 30.0 109980 0.0181 0.8477 0.9203
0.0 31.0 113646 0.0179 0.8484 0.9177
0.001 32.0 117312 0.0170 0.8485 0.9104
0.0007 33.0 120978 0.0184 0.8471 0.9113
0.0013 34.0 124644 0.0193 0.8487 0.9209
0.0016 35.0 128310 0.0169 0.8491 0.9182
0.0005 36.0 131976 0.0180 0.8476 0.9167
0.0016 37.0 135642 0.0212 0.8478 0.9239
0.0014 38.0 139308 0.0211 0.8455 0.9164
0.0 39.0 142974 0.0203 0.8468 0.9211
0.0 40.0 146640 0.0224 0.8462 0.9229

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1