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README.md
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---
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license: apache-2.0
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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-dogs
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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-dogs
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This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1696
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- Accuracy: 0.9607
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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: 10
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- eval_batch_size: 4
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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: 10
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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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| 1.2208 | 1.0 | 591 | 0.3024 | 0.9343 |
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| 0.4149 | 2.0 | 1182 | 0.2548 | 0.9268 |
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| 0.3095 | 3.0 | 1773 | 0.2700 | 0.9329 |
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| 0.2928 | 4.0 | 2364 | 0.1921 | 0.9444 |
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| 0.2352 | 5.0 | 2955 | 0.1947 | 0.9472 |
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| 0.1731 | 6.0 | 3546 | 0.2024 | 0.9458 |
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| 0.1778 | 7.0 | 4137 | 0.1967 | 0.9526 |
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| 0.156 | 8.0 | 4728 | 0.1780 | 0.9546 |
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| 0.135 | 9.0 | 5319 | 0.1818 | 0.9553 |
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| 0.1403 | 10.0 | 5910 | 0.1696 | 0.9607 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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