Model save
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README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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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: cifar100-vit-base-patch16-224-in21k
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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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# cifar100-vit-base-patch16-224-in21k
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3032
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- Accuracy: 0.9269
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 1337
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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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| 1.3866 | 1.0 | 5313 | 1.0968 | 0.8747 |
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| 0.6479 | 2.0 | 10626 | 0.4377 | 0.9004 |
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| 0.6092 | 3.0 | 15939 | 0.3439 | 0.9081 |
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| 0.4173 | 4.0 | 21252 | 0.3205 | 0.9169 |
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| 0.4665 | 5.0 | 26565 | 0.3039 | 0.9175 |
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| 0.3944 | 6.0 | 31878 | 0.3082 | 0.9201 |
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| 0.303 | 7.0 | 37191 | 0.3011 | 0.9241 |
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| 0.6128 | 8.0 | 42504 | 0.2983 | 0.9261 |
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| 0.3794 | 9.0 | 47817 | 0.2945 | 0.926 |
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| 0.3274 | 10.0 | 53130 | 0.3032 | 0.9269 |
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### Framework versions
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- Transformers 4.38.0
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- Pytorch 2.1.2+cu118
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- Datasets 2.19.1
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- Tokenizers 0.15.2
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model.safetensors
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