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segformer-b0-finetuned-segments-stamp-verification

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  1. README.md +89 -0
  2. config.json +78 -0
  3. model.safetensors +3 -0
  4. runs/May06_20-41-59_156e37e4aa66/events.out.tfevents.1715028135.156e37e4aa66.10032.0 +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-verification
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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-verification
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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: 0.0535
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+ - Mean Iou: 0.1317
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+ - Mean Accuracy: 0.2635
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+ - Overall Accuracy: 0.2635
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Stamp: 0.2635
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+ - Iou Unlabeled: 0.0
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+ - Iou Stamp: 0.2635
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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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+ | 0.6502 | 0.8333 | 20 | 0.6958 | 0.4685 | 0.9370 | 0.9370 | nan | 0.9370 | 0.0 | 0.9370 |
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+ | 0.4529 | 1.6667 | 40 | 0.5458 | 0.0754 | 0.1508 | 0.1508 | nan | 0.1508 | 0.0 | 0.1508 |
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+ | 0.3716 | 2.5 | 60 | 0.3818 | 0.0021 | 0.0041 | 0.0041 | nan | 0.0041 | 0.0 | 0.0041 |
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+ | 0.3238 | 3.3333 | 80 | 0.2932 | 0.0126 | 0.0252 | 0.0252 | nan | 0.0252 | 0.0 | 0.0252 |
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+ | 0.2167 | 4.1667 | 100 | 0.2326 | 0.0008 | 0.0015 | 0.0015 | nan | 0.0015 | 0.0 | 0.0015 |
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+ | 0.1948 | 5.0 | 120 | 0.2029 | 0.0033 | 0.0065 | 0.0065 | nan | 0.0065 | 0.0 | 0.0065 |
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+ | 0.1643 | 5.8333 | 140 | 0.1609 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 |
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+ | 0.1642 | 6.6667 | 160 | 0.1428 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 |
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+ | 0.1326 | 7.5 | 180 | 0.1222 | 0.0001 | 0.0002 | 0.0002 | nan | 0.0002 | 0.0 | 0.0002 |
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+ | 0.1012 | 8.3333 | 200 | 0.0981 | 0.0 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 |
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+ | 0.0981 | 9.1667 | 220 | 0.0972 | 0.0058 | 0.0117 | 0.0117 | nan | 0.0117 | 0.0 | 0.0117 |
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+ | 0.0838 | 10.0 | 240 | 0.0781 | 0.0015 | 0.0031 | 0.0031 | nan | 0.0031 | 0.0 | 0.0031 |
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+ | 0.0771 | 10.8333 | 260 | 0.0708 | 0.0060 | 0.0120 | 0.0120 | nan | 0.0120 | 0.0 | 0.0120 |
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+ | 0.0743 | 11.6667 | 280 | 0.0696 | 0.0298 | 0.0596 | 0.0596 | nan | 0.0596 | 0.0 | 0.0596 |
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+ | 0.0655 | 12.5 | 300 | 0.0630 | 0.0398 | 0.0795 | 0.0795 | nan | 0.0795 | 0.0 | 0.0795 |
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+ | 0.0673 | 13.3333 | 320 | 0.0613 | 0.0856 | 0.1712 | 0.1712 | nan | 0.1712 | 0.0 | 0.1712 |
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+ | 0.0573 | 14.1667 | 340 | 0.0538 | 0.0725 | 0.1450 | 0.1450 | nan | 0.1450 | 0.0 | 0.1450 |
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+ | 0.0623 | 15.0 | 360 | 0.0543 | 0.1008 | 0.2016 | 0.2016 | nan | 0.2016 | 0.0 | 0.2016 |
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+ | 0.0557 | 15.8333 | 380 | 0.0559 | 0.1474 | 0.2947 | 0.2947 | nan | 0.2947 | 0.0 | 0.2947 |
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+ | 0.0594 | 16.6667 | 400 | 0.0492 | 0.1019 | 0.2039 | 0.2039 | nan | 0.2039 | 0.0 | 0.2039 |
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+ | 0.056 | 17.5 | 420 | 0.0479 | 0.1235 | 0.2470 | 0.2470 | nan | 0.2470 | 0.0 | 0.2470 |
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+ | 0.0499 | 18.3333 | 440 | 0.0481 | 0.1124 | 0.2248 | 0.2248 | nan | 0.2248 | 0.0 | 0.2248 |
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+ | 0.0516 | 19.1667 | 460 | 0.0477 | 0.1465 | 0.2930 | 0.2930 | nan | 0.2930 | 0.0 | 0.2930 |
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+ | 0.0517 | 20.0 | 480 | 0.0535 | 0.1317 | 0.2635 | 0.2635 | nan | 0.2635 | 0.0 | 0.2635 |
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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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+ "id2label": {
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+ "0": "unlabeled",
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+ "1": "stamp"
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+ },
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+ "initializer_range": 0.02,
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