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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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- image-classification
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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: vit-base-oxford-iiit-pets
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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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# vit-base-oxford-iiit-pets
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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 pcuenq/oxford-pets dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1861
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- Accuracy: 0.9459
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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: 0.0003
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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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: 5
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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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| 0.391 | 1.0 | 370 | 0.3147 | 0.9188 |
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| 0.2372 | 2.0 | 740 | 0.2336 | 0.9296 |
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| 0.1759 | 3.0 | 1110 | 0.2081 | 0.9364 |
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| 0.1369 | 4.0 | 1480 | 0.1964 | 0.9378 |
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| 0.1154 | 5.0 | 1850 | 0.1951 | 0.9391 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 2.2.1+cu118
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- Datasets 2.16.1
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- Tokenizers 0.19.1
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