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README.md
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---
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library_name: transformers
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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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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1773
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- Accuracy: 0.9432
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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| 0.3928 | 1.0 | 370 | 0.2696 | 0.9323 |
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| 0.206 | 2.0 | 740 | 0.2022 | 0.9405 |
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| 0.1689 | 3.0 | 1110 | 0.1863 | 0.9405 |
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| 0.1298 | 4.0 | 1480 | 0.1801 | 0.9472 |
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| 0.1358 | 5.0 | 1850 | 0.1783 | 0.9418 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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runs/Dec17_01-52-47_2f5710ed6d2f/events.out.tfevents.1734400972.2f5710ed6d2f.282.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf756b3f047fa22f1f1f2dac8a5cba477274efa901c000f2d8672bd30ef05daa
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size 411
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