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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: WinKawaks/vit-tiny-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: KDRSSC_ViT2TinyViT
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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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+ # KDRSSC_ViT2TinyViT
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+
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+ This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4414
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+ - Accuracy: 0.9381
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+ - Precision: 0.9385
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+ - Recall: 0.9385
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+ - F1: 0.9382
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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: 128
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+ - eval_batch_size: 128
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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: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.9089 | 1.0 | 148 | 0.5624 | 0.906 | 0.9072 | 0.9014 | 0.8987 |
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+ | 0.4816 | 2.0 | 296 | 0.4759 | 0.94 | 0.9411 | 0.9389 | 0.9382 |
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+ | 0.3958 | 3.0 | 444 | 0.4354 | 0.952 | 0.9503 | 0.9510 | 0.9496 |
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+ | 0.3574 | 4.0 | 592 | 0.4273 | 0.949 | 0.9475 | 0.9470 | 0.9460 |
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+ | 0.3406 | 5.0 | 740 | 0.4132 | 0.955 | 0.9548 | 0.9522 | 0.9523 |
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+ | 0.3341 | 6.0 | 888 | 0.4164 | 0.951 | 0.9481 | 0.9503 | 0.9477 |
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+ | 0.3314 | 7.0 | 1036 | 0.4087 | 0.957 | 0.9545 | 0.9538 | 0.9530 |
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+ | 0.3302 | 8.0 | 1184 | 0.4075 | 0.955 | 0.9528 | 0.9517 | 0.9512 |
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+ | 0.3295 | 9.0 | 1332 | 0.4067 | 0.956 | 0.9533 | 0.9533 | 0.9522 |
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+ | 0.3292 | 10.0 | 1480 | 0.4071 | 0.956 | 0.9534 | 0.9533 | 0.9522 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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