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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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<!-- 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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# Train-Test-Augmentation-V5-beit-base |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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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