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BEiT-TO-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-TO-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: 0.8225806451612904
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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-TO-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: 0.6616
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+ - Accuracy: 0.8226
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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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+ | 1.5028 | 0.97 | 14 | 1.3862 | 0.1452 |
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+ | 1.3358 | 2.0 | 29 | 1.0831 | 0.8065 |
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+ | 0.8919 | 2.97 | 43 | 0.8097 | 0.8226 |
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+ | 0.7328 | 4.0 | 58 | 0.6546 | 0.7742 |
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+ | 0.4881 | 4.97 | 72 | 0.4860 | 0.8226 |
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+ | 0.4367 | 6.0 | 87 | 0.4770 | 0.8548 |
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+ | 0.3343 | 6.97 | 101 | 0.3912 | 0.8548 |
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+ | 0.2794 | 8.0 | 116 | 0.3226 | 0.9032 |
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+ | 0.2424 | 8.97 | 130 | 0.6426 | 0.7903 |
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+ | 0.2875 | 10.0 | 145 | 0.4604 | 0.8710 |
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+ | 0.226 | 10.97 | 159 | 0.3026 | 0.8548 |
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+ | 0.1819 | 12.0 | 174 | 0.3875 | 0.8710 |
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+ | 0.2354 | 12.97 | 188 | 0.3413 | 0.9032 |
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+ | 0.2264 | 14.0 | 203 | 0.3948 | 0.8871 |
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+ | 0.1652 | 14.97 | 217 | 0.3650 | 0.8710 |
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+ | 0.1449 | 16.0 | 232 | 0.3611 | 0.8871 |
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+ | 0.0993 | 16.97 | 246 | 0.4574 | 0.8710 |
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+ | 0.1566 | 18.0 | 261 | 0.3924 | 0.8871 |
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+ | 0.1399 | 18.97 | 275 | 0.4828 | 0.8548 |
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+ | 0.1025 | 20.0 | 290 | 0.5377 | 0.8710 |
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+ | 0.0855 | 20.97 | 304 | 0.4958 | 0.8548 |
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+ | 0.1419 | 22.0 | 319 | 0.6156 | 0.8387 |
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+ | 0.117 | 22.97 | 333 | 0.4915 | 0.8710 |
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+ | 0.0905 | 24.0 | 348 | 0.5897 | 0.8710 |
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+ | 0.1199 | 24.97 | 362 | 0.4871 | 0.8710 |
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+ | 0.1246 | 26.0 | 377 | 0.4824 | 0.8548 |
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+ | 0.0967 | 26.97 | 391 | 0.7484 | 0.8065 |
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+ | 0.1025 | 28.0 | 406 | 0.6974 | 0.8387 |
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+ | 0.1112 | 28.97 | 420 | 0.6391 | 0.8226 |
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+ | 0.0715 | 30.0 | 435 | 0.6585 | 0.8226 |
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+ | 0.085 | 30.97 | 449 | 0.7087 | 0.8065 |
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+ | 0.1032 | 32.0 | 464 | 0.6094 | 0.8387 |
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+ | 0.0836 | 32.97 | 478 | 0.5578 | 0.8065 |
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+ | 0.0716 | 34.0 | 493 | 0.5497 | 0.8710 |
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+ | 0.069 | 34.97 | 507 | 0.5093 | 0.8710 |
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+ | 0.0577 | 36.0 | 522 | 0.5189 | 0.8710 |
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+ | 0.0882 | 36.97 | 536 | 0.6531 | 0.8226 |
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+ | 0.0563 | 38.0 | 551 | 0.6661 | 0.8226 |
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+ | 0.0841 | 38.62 | 560 | 0.6616 | 0.8226 |
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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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