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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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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: vit-base-patch16-224-RU4-40
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: validation
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8333333333333334
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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-patch16-224-RU4-40
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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6467
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- Accuracy: 0.8333
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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: 5.5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 40
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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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| 1.3822 | 0.99 | 19 | 1.3130 | 0.4833 |
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| 1.2724 | 1.97 | 38 | 1.0987 | 0.6 |
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| 0.9711 | 2.96 | 57 | 0.8624 | 0.6667 |
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| 0.6349 | 4.0 | 77 | 0.7397 | 0.7333 |
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| 0.4068 | 4.99 | 96 | 0.6979 | 0.75 |
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| 0.2877 | 5.97 | 115 | 0.6270 | 0.7833 |
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| 0.2217 | 6.96 | 134 | 0.6467 | 0.8333 |
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| 0.195 | 8.0 | 154 | 0.6858 | 0.7833 |
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| 0.1392 | 8.99 | 173 | 0.6505 | 0.8167 |
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| 0.1534 | 9.97 | 192 | 0.6320 | 0.8167 |
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| 0.1136 | 10.96 | 211 | 0.8346 | 0.7833 |
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| 0.1025 | 12.0 | 231 | 0.6810 | 0.8 |
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| 0.0894 | 12.99 | 250 | 0.8258 | 0.7667 |
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| 0.1308 | 13.97 | 269 | 0.9456 | 0.75 |
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| 0.0836 | 14.96 | 288 | 0.9084 | 0.8 |
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| 0.0813 | 16.0 | 308 | 0.8688 | 0.8167 |
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| 0.1017 | 16.99 | 327 | 0.8609 | 0.8 |
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| 0.076 | 17.97 | 346 | 0.9015 | 0.8 |
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| 0.0726 | 18.96 | 365 | 0.9918 | 0.7833 |
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| 0.0549 | 20.0 | 385 | 0.9064 | 0.8 |
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| 0.0676 | 20.99 | 404 | 0.8819 | 0.75 |
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| 0.0717 | 21.97 | 423 | 0.8607 | 0.8167 |
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| 0.0547 | 22.96 | 442 | 0.8859 | 0.8 |
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| 0.0466 | 24.0 | 462 | 0.9328 | 0.8167 |
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| 0.0715 | 24.99 | 481 | 1.0178 | 0.7667 |
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| 0.0446 | 25.97 | 500 | 1.0094 | 0.7667 |
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| 0.0468 | 26.96 | 519 | 0.9175 | 0.8167 |
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| 0.0458 | 28.0 | 539 | 0.8580 | 0.8 |
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| 0.0392 | 28.99 | 558 | 1.0589 | 0.7833 |
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| 0.0469 | 29.97 | 577 | 1.0905 | 0.8 |
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| 0.0425 | 30.96 | 596 | 1.0078 | 0.7833 |
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| 0.0464 | 32.0 | 616 | 1.0206 | 0.7833 |
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| 0.0336 | 32.99 | 635 | 0.9653 | 0.8167 |
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| 0.0302 | 33.97 | 654 | 0.9574 | 0.8 |
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| 0.0353 | 34.96 | 673 | 0.9621 | 0.8167 |
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| 0.0344 | 36.0 | 693 | 0.9792 | 0.8167 |
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| 0.0195 | 36.99 | 712 | 0.9459 | 0.8167 |
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| 0.031 | 37.97 | 731 | 0.9488 | 0.8167 |
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| 0.0224 | 38.96 | 750 | 0.9440 | 0.8167 |
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| 0.0309 | 39.48 | 760 | 0.9448 | 0.8167 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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