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BEiT-DMAE-DA

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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: microsoft/beit-base-patch16-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: BEiT-DMAE-DA
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8260869565217391
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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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+ # BEiT-DMAE-DA
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5902
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+ - Accuracy: 0.8261
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 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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+ | 1.3475 | 0.96 | 11 | 1.3279 | 0.3261 |
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+ | 1.1875 | 2.0 | 23 | 1.1320 | 0.3478 |
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+ | 0.9998 | 2.96 | 34 | 0.9957 | 0.5435 |
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+ | 0.8836 | 4.0 | 46 | 0.8436 | 0.5870 |
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+ | 0.7593 | 4.96 | 57 | 0.7904 | 0.6304 |
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+ | 0.6939 | 6.0 | 69 | 0.6656 | 0.8261 |
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+ | 0.4924 | 6.96 | 80 | 0.6724 | 0.6739 |
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+ | 0.4444 | 8.0 | 92 | 0.5951 | 0.7826 |
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+ | 0.337 | 8.96 | 103 | 0.5222 | 0.8261 |
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+ | 0.3213 | 10.0 | 115 | 0.6814 | 0.8043 |
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+ | 0.2689 | 10.96 | 126 | 0.5913 | 0.7826 |
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+ | 0.2538 | 12.0 | 138 | 0.6228 | 0.7826 |
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+ | 0.2032 | 12.96 | 149 | 0.6992 | 0.7609 |
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+ | 0.2152 | 14.0 | 161 | 0.7730 | 0.7609 |
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+ | 0.1713 | 14.96 | 172 | 0.7762 | 0.7609 |
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+ | 0.2042 | 16.0 | 184 | 0.7652 | 0.7174 |
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+ | 0.1668 | 16.96 | 195 | 0.5512 | 0.8478 |
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+ | 0.1743 | 18.0 | 207 | 0.7311 | 0.7826 |
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+ | 0.1226 | 18.96 | 218 | 0.7115 | 0.8043 |
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+ | 0.1537 | 20.0 | 230 | 0.6800 | 0.7609 |
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+ | 0.1311 | 20.96 | 241 | 0.5864 | 0.8478 |
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+ | 0.1335 | 22.0 | 253 | 0.6346 | 0.8261 |
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+ | 0.0981 | 22.96 | 264 | 0.6541 | 0.8043 |
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+ | 0.1248 | 24.0 | 276 | 0.7017 | 0.8261 |
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+ | 0.1183 | 24.96 | 287 | 0.6964 | 0.8261 |
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+ | 0.0946 | 26.0 | 299 | 0.6450 | 0.8261 |
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+ | 0.0957 | 26.96 | 310 | 0.7057 | 0.8043 |
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+ | 0.1692 | 28.0 | 322 | 0.6635 | 0.8043 |
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+ | 0.0967 | 28.96 | 333 | 0.5040 | 0.8696 |
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+ | 0.094 | 30.0 | 345 | 0.5588 | 0.8913 |
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+ | 0.0843 | 30.96 | 356 | 0.5398 | 0.8696 |
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+ | 0.0851 | 32.0 | 368 | 0.5806 | 0.8478 |
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+ | 0.0955 | 32.96 | 379 | 0.4816 | 0.9130 |
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+ | 0.1157 | 34.0 | 391 | 0.5289 | 0.8696 |
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+ | 0.072 | 34.96 | 402 | 0.5657 | 0.8913 |
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+ | 0.091 | 36.0 | 414 | 0.5566 | 0.8478 |
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+ | 0.0891 | 36.96 | 425 | 0.5729 | 0.8478 |
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+ | 0.0732 | 38.0 | 437 | 0.5915 | 0.8261 |
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+ | 0.0647 | 38.26 | 440 | 0.5902 | 0.8261 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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