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3class_EfficientNetv2_ForTesting

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  1. README.md +108 -0
  2. config.json +24 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: 3class_EfficientNetv2_ForTesting
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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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+ # 3class_EfficientNetv2_ForTesting
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0790
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+ - Precision: 0.9729
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+ - Recall: 0.9732
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+ - Accuracy: 0.9773
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+ - F1: 0.9730
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+ - Roc Auc: 0.9983
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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: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - num_epochs: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | Roc Auc |
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+ |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|:-------:|
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+ | 0.5084 | 0.0466 | 30 | 0.4056 | 0.8538 | 0.8639 | 0.8716 | 0.8536 | 0.9726 |
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+ | 0.3707 | 0.0932 | 60 | 0.2457 | 0.9072 | 0.9170 | 0.9223 | 0.9101 | 0.9855 |
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+ | 0.2629 | 0.1398 | 90 | 0.2060 | 0.9168 | 0.9135 | 0.9266 | 0.9147 | 0.9886 |
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+ | 0.2108 | 0.1863 | 120 | 0.1867 | 0.9198 | 0.9277 | 0.9345 | 0.9226 | 0.9905 |
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+ | 0.2370 | 0.2329 | 150 | 0.1687 | 0.9263 | 0.9320 | 0.9389 | 0.9281 | 0.9911 |
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+ | 0.1325 | 0.2795 | 180 | 0.1441 | 0.9449 | 0.9323 | 0.9485 | 0.9378 | 0.9925 |
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+ | 0.1487 | 0.3261 | 210 | 0.1196 | 0.9424 | 0.9481 | 0.9528 | 0.9446 | 0.9956 |
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+ | 0.0947 | 0.3727 | 240 | 0.1068 | 0.9639 | 0.9611 | 0.9686 | 0.9624 | 0.9951 |
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+ | 0.1918 | 0.4193 | 270 | 0.1037 | 0.9634 | 0.9538 | 0.9659 | 0.9581 | 0.9960 |
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+ | 0.0833 | 0.4658 | 300 | 0.1083 | 0.9518 | 0.9517 | 0.9598 | 0.9517 | 0.9959 |
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+ | 0.1856 | 0.5124 | 330 | 0.0996 | 0.9541 | 0.9587 | 0.9633 | 0.9561 | 0.9970 |
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+ | 0.1917 | 0.5590 | 360 | 0.0979 | 0.9562 | 0.9581 | 0.9633 | 0.9569 | 0.9968 |
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+ | 0.1097 | 0.6056 | 390 | 0.1035 | 0.9601 | 0.9542 | 0.9642 | 0.9570 | 0.9961 |
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+ | 0.2180 | 0.6522 | 420 | 0.0829 | 0.9681 | 0.9689 | 0.9738 | 0.9684 | 0.9976 |
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+ | 0.1316 | 0.6988 | 450 | 0.0999 | 0.9627 | 0.9672 | 0.9703 | 0.9647 | 0.9971 |
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+ | 0.1480 | 0.7453 | 480 | 0.0833 | 0.9756 | 0.9710 | 0.9773 | 0.9732 | 0.9974 |
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+ | 0.0660 | 0.7919 | 510 | 0.0757 | 0.9733 | 0.9622 | 0.9729 | 0.9672 | 0.9979 |
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+ | 0.1069 | 0.8385 | 540 | 0.0664 | 0.9765 | 0.9745 | 0.9799 | 0.9755 | 0.9979 |
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+ | 0.0718 | 0.8851 | 570 | 0.0725 | 0.9777 | 0.9713 | 0.9782 | 0.9744 | 0.9979 |
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+ | 0.0738 | 0.9317 | 600 | 0.0786 | 0.9772 | 0.9670 | 0.9764 | 0.9717 | 0.9981 |
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+ | 0.0914 | 0.9783 | 630 | 0.0747 | 0.9795 | 0.9748 | 0.9808 | 0.9770 | 0.9977 |
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+ | 0.0299 | 1.0248 | 660 | 0.0812 | 0.9732 | 0.9726 | 0.9773 | 0.9729 | 0.9979 |
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+ | 0.0185 | 1.0714 | 690 | 0.0608 | 0.9781 | 0.9740 | 0.9799 | 0.9760 | 0.9985 |
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+ | 0.0603 | 1.1180 | 720 | 0.0776 | 0.9750 | 0.9777 | 0.9799 | 0.9762 | 0.9983 |
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+ | 0.0492 | 1.1646 | 750 | 0.0720 | 0.9762 | 0.9761 | 0.9799 | 0.9761 | 0.9982 |
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+ | 0.0304 | 1.2112 | 780 | 0.0738 | 0.9737 | 0.9750 | 0.9782 | 0.9743 | 0.9982 |
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+ | 0.0532 | 1.2578 | 810 | 0.0678 | 0.9740 | 0.9697 | 0.9764 | 0.9718 | 0.9983 |
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+ | 0.0618 | 1.3043 | 840 | 0.0805 | 0.9750 | 0.9716 | 0.9773 | 0.9732 | 0.9981 |
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+ | 0.0361 | 1.3509 | 870 | 0.0831 | 0.9715 | 0.9710 | 0.9755 | 0.9712 | 0.9982 |
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+ | 0.0207 | 1.3975 | 900 | 0.0703 | 0.9746 | 0.9734 | 0.9782 | 0.9740 | 0.9985 |
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+ | 0.0487 | 1.4441 | 930 | 0.0771 | 0.9739 | 0.9726 | 0.9773 | 0.9732 | 0.9983 |
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+ | 0.0374 | 1.4907 | 960 | 0.0760 | 0.9746 | 0.9734 | 0.9782 | 0.9740 | 0.9983 |
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+ | 0.0730 | 1.5373 | 990 | 0.0811 | 0.9724 | 0.9737 | 0.9773 | 0.9730 | 0.9983 |
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+ | 0.0659 | 1.5839 | 1020 | 0.0755 | 0.9773 | 0.9751 | 0.9799 | 0.9762 | 0.9983 |
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+ | 0.0645 | 1.6304 | 1050 | 0.0802 | 0.9704 | 0.9716 | 0.9755 | 0.9709 | 0.9984 |
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+ | 0.0497 | 1.6770 | 1080 | 0.0726 | 0.9772 | 0.9751 | 0.9799 | 0.9761 | 0.9984 |
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+ | 0.0374 | 1.7236 | 1110 | 0.0751 | 0.9752 | 0.9734 | 0.9782 | 0.9743 | 0.9983 |
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+ | 0.0310 | 1.7702 | 1140 | 0.0710 | 0.9789 | 0.9753 | 0.9808 | 0.9771 | 0.9984 |
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+ | 0.0304 | 1.8168 | 1170 | 0.0702 | 0.9728 | 0.9732 | 0.9773 | 0.9729 | 0.9985 |
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+ | 0.0072 | 1.8634 | 1200 | 0.0729 | 0.9775 | 0.9769 | 0.9808 | 0.9772 | 0.9984 |
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+ | 0.0094 | 1.9099 | 1230 | 0.0718 | 0.9762 | 0.9761 | 0.9799 | 0.9761 | 0.9984 |
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+ | 0.0413 | 1.9565 | 1260 | 0.0790 | 0.9729 | 0.9732 | 0.9773 | 0.9730 | 0.9983 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.3.0
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+ - Pytorch 2.10.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.2
config.json ADDED
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+ {
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+ "architectures": [
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+ "UniversalVisionModel"
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+ ],
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+ "auto_map": {
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+ "AutoConfig": "modeling_universal_vision.UniversalVisionConfig",
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+ "AutoModelForImageClassification": "modeling_universal_vision.UniversalVisionModel"
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+ },
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+ "backbone_name": "tf_efficientnetv2_s.in1k",
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+ "dtype": "float32",
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "model_type": "universal_vision",
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+ "transformers_version": "5.3.0",
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+ "use_cache": false
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+ }
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