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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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datasets: |
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- cifar10 |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-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: cifar10 |
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type: cifar10 |
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config: plain_text |
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split: train |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.106 |
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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-cifar10 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cifar10 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3302 |
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- Accuracy: 0.106 |
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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: 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: 10.0 |
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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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| 2.3324 | 1.0 | 664 | 2.3352 | 0.0967 | |
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| 2.3489 | 2.0 | 1328 | 2.3288 | 0.1049 | |
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| 2.4899 | 3.0 | 1992 | 2.4473 | 0.0989 | |
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| 2.479 | 4.0 | 2656 | 2.4894 | 0.1 | |
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| 2.4179 | 5.0 | 3320 | 2.4404 | 0.0947 | |
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| 2.3881 | 6.0 | 3984 | 2.3931 | 0.102 | |
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| 2.3597 | 7.0 | 4648 | 2.3744 | 0.0967 | |
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| 2.3721 | 8.0 | 5312 | 2.3667 | 0.0935 | |
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| 2.3456 | 9.0 | 5976 | 2.3495 | 0.1036 | |
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| 2.3361 | 10.0 | 6640 | 2.3473 | 0.1025 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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