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--- |
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license: apache-2.0 |
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base_model: google/vit-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: vit-base-patch16-224-finetuned-cifar10 |
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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: train |
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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: 0.9844 |
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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-cifar10 |
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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: 0.0564 |
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- Accuracy: 0.9844 |
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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: 1 |
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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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| 2.4597 | 0.03 | 10 | 2.2902 | 0.1662 | |
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| 2.1429 | 0.06 | 20 | 1.7855 | 0.5086 | |
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| 1.6466 | 0.09 | 30 | 1.0829 | 0.8484 | |
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| 0.9962 | 0.11 | 40 | 0.4978 | 0.9288 | |
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| 0.6127 | 0.14 | 50 | 0.2717 | 0.9508 | |
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| 0.4544 | 0.17 | 60 | 0.1942 | 0.9588 | |
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| 0.4352 | 0.2 | 70 | 0.1504 | 0.9672 | |
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| 0.374 | 0.23 | 80 | 0.1221 | 0.9718 | |
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| 0.3261 | 0.26 | 90 | 0.1057 | 0.9772 | |
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| 0.34 | 0.28 | 100 | 0.0943 | 0.979 | |
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| 0.284 | 0.31 | 110 | 0.0958 | 0.9754 | |
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| 0.3151 | 0.34 | 120 | 0.0866 | 0.9776 | |
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| 0.3004 | 0.37 | 130 | 0.0838 | 0.9788 | |
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| 0.3334 | 0.4 | 140 | 0.0798 | 0.9806 | |
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| 0.3018 | 0.43 | 150 | 0.0800 | 0.9778 | |
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| 0.2957 | 0.45 | 160 | 0.0749 | 0.9808 | |
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| 0.2952 | 0.48 | 170 | 0.0704 | 0.9814 | |
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| 0.3084 | 0.51 | 180 | 0.0720 | 0.9812 | |
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| 0.3015 | 0.54 | 190 | 0.0708 | 0.983 | |
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| 0.2763 | 0.57 | 200 | 0.0672 | 0.9832 | |
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| 0.3376 | 0.6 | 210 | 0.0700 | 0.982 | |
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| 0.285 | 0.63 | 220 | 0.0657 | 0.9828 | |
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| 0.2857 | 0.65 | 230 | 0.0629 | 0.9836 | |
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| 0.2644 | 0.68 | 240 | 0.0612 | 0.9842 | |
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| 0.2461 | 0.71 | 250 | 0.0601 | 0.9836 | |
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| 0.2802 | 0.74 | 260 | 0.0589 | 0.9842 | |
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| 0.2481 | 0.77 | 270 | 0.0604 | 0.9838 | |
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| 0.2641 | 0.8 | 280 | 0.0591 | 0.9846 | |
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| 0.2737 | 0.82 | 290 | 0.0581 | 0.9842 | |
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| 0.2391 | 0.85 | 300 | 0.0565 | 0.9852 | |
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| 0.2283 | 0.88 | 310 | 0.0558 | 0.986 | |
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| 0.2626 | 0.91 | 320 | 0.0559 | 0.9852 | |
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| 0.2325 | 0.94 | 330 | 0.0563 | 0.9846 | |
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| 0.2459 | 0.97 | 340 | 0.0565 | 0.9846 | |
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| 0.2474 | 1.0 | 350 | 0.0564 | 0.9844 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.1 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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