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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
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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: 0.1883
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- Accuracy: 0.9540
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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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| 0.3824 | 1.0 | 370 | 0.2976 | 0.9310 |
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| 0.1977 | 2.0 | 740 | 0.2266 | 0.9378 |
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| 0.1885 | 3.0 | 1110 | 0.2039 | 0.9378 |
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| 0.1288 | 4.0 | 1480 | 0.1941 | 0.9405 |
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| 0.1368 | 5.0 | 1850 | 0.1894 | 0.9418 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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runs/Apr29_12-00-04_d69a927e8dde/events.out.tfevents.1714393131.d69a927e8dde.5447.4
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version https://git-lfs.github.com/spec/v1
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oid sha256:2243a76d6e59b53ef84ce17dec0a1422f795c6f89bb6f1a6e274d5c65eeaa452
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size 411
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