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End of training

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  2. model.safetensors +1 -1
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-pt22k-ft22k
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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: Train-Test-Augmentation-V5-beit-base
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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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+ # Train-Test-Augmentation-V5-beit-base
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6899
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+ - Accuracy: 0.8442
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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: 15
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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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+ | 1.0473 | 1.0 | 55 | 0.8312 | 0.7759 |
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+ | 0.3767 | 2.0 | 110 | 0.5476 | 0.8336 |
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+ | 0.176 | 3.0 | 165 | 0.5248 | 0.8256 |
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+ | 0.07 | 4.0 | 220 | 0.5597 | 0.8527 |
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+ | 0.043 | 5.0 | 275 | 0.5707 | 0.8472 |
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+ | 0.0272 | 6.0 | 330 | 0.6225 | 0.8264 |
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+ | 0.0168 | 7.0 | 385 | 0.5721 | 0.8553 |
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+ | 0.0076 | 8.0 | 440 | 0.5967 | 0.8608 |
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+ | 0.006 | 9.0 | 495 | 0.7036 | 0.8272 |
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+ | 0.007 | 10.0 | 550 | 0.7167 | 0.8400 |
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+ | 0.0048 | 11.0 | 605 | 0.6734 | 0.8506 |
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+ | 0.0023 | 12.0 | 660 | 0.7424 | 0.8332 |
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+ | 0.0032 | 13.0 | 715 | 0.7283 | 0.8340 |
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+ | 0.002 | 14.0 | 770 | 0.6805 | 0.8502 |
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+ | 0.0021 | 15.0 | 825 | 0.6899 | 0.8442 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.1
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+ - Tokenizers 0.15.2
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