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segformer-b0-finetuned-segments-stamp-verification2

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  1. README.md +89 -0
  2. config.json +78 -0
  3. model.safetensors +3 -0
  4. runs/May07_06-19-03_e951751501eb/events.out.tfevents.1715062756.e951751501eb.6709.0 +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: other
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+ base_model: nvidia/mit-b0
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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-b0-finetuned-segments-stamp-verification2
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+ results: []
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+ ---
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+
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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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+
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+ # segformer-b0-finetuned-segments-stamp-verification2
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the AliShah07/stamp-verification dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0365
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+ - Mean Iou: 0.1372
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+ - Mean Accuracy: 0.2744
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+ - Overall Accuracy: 0.2744
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Stamp: 0.2744
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+ - Iou Unlabeled: 0.0
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+ - Iou Stamp: 0.2744
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Stamp | Iou Unlabeled | Iou Stamp |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:|
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+ | 0.4566 | 0.8333 | 20 | 0.4738 | 0.1430 | 0.2860 | 0.2860 | nan | 0.2860 | 0.0 | 0.2860 |
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+ | 0.3076 | 1.6667 | 40 | 0.3046 | 0.1307 | 0.2614 | 0.2614 | nan | 0.2614 | 0.0 | 0.2614 |
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+ | 0.2373 | 2.5 | 60 | 0.2226 | 0.0604 | 0.1209 | 0.1209 | nan | 0.1209 | 0.0 | 0.1209 |
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+ | 0.2184 | 3.3333 | 80 | 0.2220 | 0.1942 | 0.3884 | 0.3884 | nan | 0.3884 | 0.0 | 0.3884 |
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+ | 0.1578 | 4.1667 | 100 | 0.1704 | 0.2468 | 0.4936 | 0.4936 | nan | 0.4936 | 0.0 | 0.4936 |
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+ | 0.1412 | 5.0 | 120 | 0.1269 | 0.0376 | 0.0751 | 0.0751 | nan | 0.0751 | 0.0 | 0.0751 |
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+ | 0.1109 | 5.8333 | 140 | 0.1076 | 0.2741 | 0.5483 | 0.5483 | nan | 0.5483 | 0.0 | 0.5483 |
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+ | 0.106 | 6.6667 | 160 | 0.0892 | 0.0583 | 0.1166 | 0.1166 | nan | 0.1166 | 0.0 | 0.1166 |
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+ | 0.0899 | 7.5 | 180 | 0.0747 | 0.0173 | 0.0346 | 0.0346 | nan | 0.0346 | 0.0 | 0.0346 |
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+ | 0.0794 | 8.3333 | 200 | 0.0683 | 0.0189 | 0.0378 | 0.0378 | nan | 0.0378 | 0.0 | 0.0378 |
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+ | 0.0741 | 9.1667 | 220 | 0.0639 | 0.0981 | 0.1963 | 0.1963 | nan | 0.1963 | 0.0 | 0.1963 |
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+ | 0.0832 | 10.0 | 240 | 0.0559 | 0.0599 | 0.1198 | 0.1198 | nan | 0.1198 | 0.0 | 0.1198 |
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+ | 0.0575 | 10.8333 | 260 | 0.0527 | 0.0769 | 0.1538 | 0.1538 | nan | 0.1538 | 0.0 | 0.1538 |
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+ | 0.05 | 11.6667 | 280 | 0.0502 | 0.0852 | 0.1704 | 0.1704 | nan | 0.1704 | 0.0 | 0.1704 |
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+ | 0.0523 | 12.5 | 300 | 0.0446 | 0.1038 | 0.2076 | 0.2076 | nan | 0.2076 | 0.0 | 0.2076 |
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+ | 0.0481 | 13.3333 | 320 | 0.0431 | 0.0956 | 0.1913 | 0.1913 | nan | 0.1913 | 0.0 | 0.1913 |
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+ | 0.0471 | 14.1667 | 340 | 0.0420 | 0.1330 | 0.2660 | 0.2660 | nan | 0.2660 | 0.0 | 0.2660 |
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+ | 0.042 | 15.0 | 360 | 0.0412 | 0.1124 | 0.2248 | 0.2248 | nan | 0.2248 | 0.0 | 0.2248 |
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+ | 0.041 | 15.8333 | 380 | 0.0400 | 0.1144 | 0.2288 | 0.2288 | nan | 0.2288 | 0.0 | 0.2288 |
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+ | 0.0444 | 16.6667 | 400 | 0.0383 | 0.1415 | 0.2830 | 0.2830 | nan | 0.2830 | 0.0 | 0.2830 |
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+ | 0.0514 | 17.5 | 420 | 0.0377 | 0.0779 | 0.1559 | 0.1559 | nan | 0.1559 | 0.0 | 0.1559 |
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+ | 0.0434 | 18.3333 | 440 | 0.0374 | 0.1482 | 0.2964 | 0.2964 | nan | 0.2964 | 0.0 | 0.2964 |
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+ | 0.0383 | 19.1667 | 460 | 0.0363 | 0.1843 | 0.3686 | 0.3686 | nan | 0.3686 | 0.0 | 0.3686 |
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+ | 0.0411 | 20.0 | 480 | 0.0365 | 0.1372 | 0.2744 | 0.2744 | nan | 0.2744 | 0.0 | 0.2744 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "nvidia/mit-b0",
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+ "architectures": [
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+ "SegformerForSemanticSegmentation"
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+ ],
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+ "hidden_act": "gelu",
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+ "hidden_sizes": [
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+ 32,
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+ ],
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+ "id2label": {
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+ "0": "unlabeled",
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.40.2"
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+ }
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