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--- |
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license: apache-2.0 |
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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: vit-base-patch16-224-finetuned-main-gpu-20e-final-1 |
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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: 0.9917517006802721 |
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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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# vit-base-patch16-224-finetuned-main-gpu-20e-final-1 |
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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 the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0272 |
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- Accuracy: 0.9918 |
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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: 20 |
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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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| 0.4776 | 1.0 | 551 | 0.4399 | 0.8125 | |
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| 0.3207 | 2.0 | 1102 | 0.2645 | 0.8978 | |
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| 0.2292 | 3.0 | 1653 | 0.1388 | 0.9468 | |
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| 0.1811 | 4.0 | 2204 | 0.0943 | 0.9662 | |
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| 0.1633 | 5.0 | 2755 | 0.0740 | 0.9723 | |
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| 0.1355 | 6.0 | 3306 | 0.0744 | 0.9727 | |
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| 0.1413 | 7.0 | 3857 | 0.0548 | 0.9813 | |
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| 0.1257 | 8.0 | 4408 | 0.0442 | 0.9844 | |
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| 0.1057 | 9.0 | 4959 | 0.0517 | 0.9821 | |
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| 0.1 | 10.0 | 5510 | 0.0376 | 0.9868 | |
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| 0.0873 | 11.0 | 6061 | 0.0410 | 0.9866 | |
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| 0.0974 | 12.0 | 6612 | 0.0430 | 0.9861 | |
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| 0.0673 | 13.0 | 7163 | 0.0421 | 0.9852 | |
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| 0.0913 | 14.0 | 7714 | 0.0339 | 0.9882 | |
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| 0.0594 | 15.0 | 8265 | 0.0327 | 0.9896 | |
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| 0.0608 | 16.0 | 8816 | 0.0379 | 0.9885 | |
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| 0.0725 | 17.0 | 9367 | 0.0288 | 0.9904 | |
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| 0.0742 | 18.0 | 9918 | 0.0284 | 0.9906 | |
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| 0.0708 | 19.0 | 10469 | 0.0273 | 0.9916 | |
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| 0.0648 | 20.0 | 11020 | 0.0272 | 0.9918 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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