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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: google/vit-base-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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+ model-index:
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+ - name: vit-base-patch16-224-dmae-va-da-40D
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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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+ # vit-base-patch16-224-dmae-va-da-40D
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4014
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+ - Accuracy: 0.8372
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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: 5e-05
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 40
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.92 | 3 | 1.2901 | 0.4186 |
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+ | No log | 1.85 | 6 | 1.2314 | 0.4419 |
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+ | No log | 2.77 | 9 | 1.1530 | 0.4651 |
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+ | 1.2976 | 4.0 | 13 | 0.9852 | 0.6047 |
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+ | 1.2976 | 4.92 | 16 | 0.8450 | 0.7674 |
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+ | 1.2976 | 5.85 | 19 | 0.8367 | 0.6512 |
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+ | 1.2976 | 6.77 | 22 | 0.7545 | 0.7209 |
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+ | 0.8294 | 8.0 | 26 | 0.6711 | 0.7907 |
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+ | 0.8294 | 8.92 | 29 | 0.6739 | 0.7209 |
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+ | 0.8294 | 9.85 | 32 | 0.6010 | 0.7442 |
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+ | 0.8294 | 10.77 | 35 | 0.5369 | 0.7442 |
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+ | 0.4293 | 12.0 | 39 | 0.5272 | 0.7907 |
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+ | 0.4293 | 12.92 | 42 | 0.5217 | 0.7442 |
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+ | 0.4293 | 13.85 | 45 | 0.4844 | 0.7674 |
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+ | 0.2695 | 14.77 | 48 | 0.4948 | 0.7907 |
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+ | 0.2695 | 16.0 | 52 | 0.4776 | 0.7674 |
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+ | 0.2695 | 16.92 | 55 | 0.4410 | 0.7907 |
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+ | 0.2695 | 17.85 | 58 | 0.4871 | 0.7442 |
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+ | 0.1905 | 18.77 | 61 | 0.4375 | 0.7907 |
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+ | 0.1905 | 20.0 | 65 | 0.4578 | 0.8140 |
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+ | 0.1905 | 20.92 | 68 | 0.4956 | 0.8140 |
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+ | 0.1905 | 21.85 | 71 | 0.4500 | 0.8140 |
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+ | 0.135 | 22.77 | 74 | 0.4071 | 0.8605 |
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+ | 0.135 | 24.0 | 78 | 0.4158 | 0.8605 |
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+ | 0.135 | 24.92 | 81 | 0.4380 | 0.8372 |
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+ | 0.1485 | 25.85 | 84 | 0.4281 | 0.8140 |
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+ | 0.1485 | 26.77 | 87 | 0.3777 | 0.8837 |
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+ | 0.1485 | 28.0 | 91 | 0.3404 | 0.9302 |
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+ | 0.1485 | 28.92 | 94 | 0.3581 | 0.9070 |
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+ | 0.1001 | 29.85 | 97 | 0.3807 | 0.8605 |
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+ | 0.1001 | 30.77 | 100 | 0.3700 | 0.8837 |
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+ | 0.1001 | 32.0 | 104 | 0.3730 | 0.8837 |
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+ | 0.1001 | 32.92 | 107 | 0.3868 | 0.8837 |
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+ | 0.0797 | 33.85 | 110 | 0.3883 | 0.8605 |
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+ | 0.0797 | 34.77 | 113 | 0.3933 | 0.8372 |
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+ | 0.0797 | 36.0 | 117 | 0.3998 | 0.8372 |
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+ | 0.0991 | 36.92 | 120 | 0.4014 | 0.8372 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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