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segformer-b1-finetuned-segments-pv

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  1. README.md +60 -12
  2. model.safetensors +1 -1
  3. runs/Jul18_16-24-12_a8126dddca68/events.out.tfevents.1721319858.a8126dddca68.24.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,12 +1,12 @@
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  ---
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- base_model: nvidia/segformer-b1-finetuned-ade-512-512
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  license: other
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- metrics:
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- - precision
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  tags:
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  - vision
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  - image-segmentation
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  - generated_from_trainer
 
 
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  model-index:
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  - name: segformer-b1-finetuned-segments-pv
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  results: []
@@ -15,15 +15,14 @@ model-index:
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/mdux6ltv)
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/mdux6ltv)
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  # segformer-b1-finetuned-segments-pv
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  This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0077
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- - Mean Iou: 0.8247
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- - Precision: 0.9129
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  ## Model description
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@@ -48,13 +47,62 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Precision |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|
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- | 0.0054 | 1.0 | 3666 | 0.0077 | 0.8247 | 0.9129 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
 
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  license: other
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+ base_model: nvidia/segformer-b1-finetuned-ade-512-512
 
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  tags:
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  - vision
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  - image-segmentation
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  - generated_from_trainer
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+ metrics:
9
+ - precision
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  model-index:
11
  - name: segformer-b1-finetuned-segments-pv
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  results: []
 
15
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/lyupah0l)
 
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  # segformer-b1-finetuned-segments-pv
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  This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0192
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+ - Mean Iou: 0.8631
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+ - Precision: 0.9304
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 50
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Precision |
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+ |:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|
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+ | 0.0051 | 1.0 | 3666 | 0.0084 | 0.8064 | 0.8864 |
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+ | 0.0038 | 2.0 | 7332 | 0.0115 | 0.7607 | 0.9338 |
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+ | 0.0001 | 3.0 | 10998 | 0.0089 | 0.8145 | 0.9115 |
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+ | 0.0 | 4.0 | 14664 | 0.0078 | 0.8317 | 0.9063 |
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+ | 0.0 | 5.0 | 18330 | 0.0093 | 0.8078 | 0.9244 |
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+ | 0.0017 | 6.0 | 21996 | 0.0080 | 0.8370 | 0.9203 |
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+ | 0.0019 | 7.0 | 25662 | 0.0085 | 0.8395 | 0.9163 |
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+ | 0.0001 | 8.0 | 29328 | 0.0099 | 0.8379 | 0.8931 |
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+ | 0.0019 | 9.0 | 32994 | 0.0100 | 0.8388 | 0.9225 |
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+ | 0.0048 | 10.0 | 36660 | 0.0103 | 0.8422 | 0.9035 |
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+ | 0.0238 | 11.0 | 40326 | 0.0132 | 0.8378 | 0.9169 |
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+ | 0.0 | 12.0 | 43992 | 0.0093 | 0.8509 | 0.9254 |
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+ | 0.0017 | 13.0 | 47658 | 0.0116 | 0.8417 | 0.9243 |
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+ | 0.0014 | 14.0 | 51324 | 0.0127 | 0.8348 | 0.9017 |
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+ | 0.0031 | 15.0 | 54990 | 0.0123 | 0.8463 | 0.9299 |
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+ | 0.0016 | 16.0 | 58656 | 0.0109 | 0.8439 | 0.9062 |
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+ | 0.0091 | 17.0 | 62322 | 0.0199 | 0.8143 | 0.9344 |
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+ | 0.0017 | 18.0 | 65988 | 0.0155 | 0.8326 | 0.9184 |
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+ | 0.0 | 19.0 | 69654 | 0.0128 | 0.8351 | 0.8971 |
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+ | 0.0013 | 20.0 | 73320 | 0.0135 | 0.8360 | 0.8970 |
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+ | 0.0015 | 21.0 | 76986 | 0.0151 | 0.8466 | 0.9055 |
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+ | 0.0011 | 22.0 | 80652 | 0.0136 | 0.8525 | 0.9117 |
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+ | 0.0016 | 23.0 | 84318 | 0.0129 | 0.8478 | 0.9052 |
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+ | 0.0007 | 24.0 | 87984 | 0.0189 | 0.8422 | 0.9422 |
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+ | 0.0012 | 25.0 | 91650 | 0.0134 | 0.8435 | 0.9070 |
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+ | 0.0012 | 26.0 | 95316 | 0.0152 | 0.8532 | 0.9243 |
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+ | 0.0028 | 27.0 | 98982 | 0.0145 | 0.8521 | 0.9273 |
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+ | 0.0023 | 28.0 | 102648 | 0.0156 | 0.8566 | 0.9288 |
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+ | 0.0 | 29.0 | 106314 | 0.0176 | 0.8494 | 0.9222 |
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+ | 0.0 | 30.0 | 109980 | 0.0156 | 0.8542 | 0.9282 |
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+ | 0.0 | 31.0 | 113646 | 0.0158 | 0.8578 | 0.9273 |
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+ | 0.0012 | 32.0 | 117312 | 0.0171 | 0.8560 | 0.9258 |
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+ | 0.0005 | 33.0 | 120978 | 0.0146 | 0.8534 | 0.9149 |
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+ | 0.0016 | 34.0 | 124644 | 0.0199 | 0.8519 | 0.9250 |
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+ | 0.0015 | 35.0 | 128310 | 0.0164 | 0.8559 | 0.9181 |
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+ | 0.0005 | 36.0 | 131976 | 0.0164 | 0.8551 | 0.9176 |
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+ | 0.0014 | 37.0 | 135642 | 0.0172 | 0.8594 | 0.9263 |
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+ | 0.0008 | 38.0 | 139308 | 0.0178 | 0.8601 | 0.9273 |
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+ | 0.0 | 39.0 | 142974 | 0.0153 | 0.8601 | 0.9281 |
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+ | 0.0 | 40.0 | 146640 | 0.0165 | 0.8632 | 0.9324 |
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+ | 0.0 | 41.0 | 150306 | 0.0172 | 0.8624 | 0.9328 |
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+ | 0.0002 | 42.0 | 153972 | 0.0201 | 0.8590 | 0.9303 |
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+ | 0.0033 | 43.0 | 157638 | 0.0180 | 0.8611 | 0.9347 |
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+ | 0.0 | 44.0 | 161304 | 0.0155 | 0.8620 | 0.9283 |
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+ | 0.0011 | 45.0 | 164970 | 0.0174 | 0.8624 | 0.9277 |
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+ | 0.0004 | 46.0 | 168636 | 0.0192 | 0.8612 | 0.9316 |
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+ | 0.0 | 47.0 | 172302 | 0.0185 | 0.8612 | 0.9232 |
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+ | 0.0007 | 48.0 | 175968 | 0.0173 | 0.8623 | 0.9247 |
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+ | 0.0007 | 49.0 | 179634 | 0.0196 | 0.8628 | 0.9295 |
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+ | 0.0003 | 50.0 | 183300 | 0.0192 | 0.8631 | 0.9304 |
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  ### Framework versions
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