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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-RU3-40
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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-RU3-40
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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: 0.5667
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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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| 1.3821 | 0.99 | 19 | 1.3119 | 0.4833 |
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| 1.2698 | 1.97 | 38 | 1.0852 | 0.6167 |
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| 0.9819 | 2.96 | 57 | 0.8757 | 0.7 |
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| 0.6671 | 4.0 | 77 | 0.7689 | 0.7333 |
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| 0.4248 | 4.99 | 96 | 0.7294 | 0.7167 |
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| 0.3005 | 5.97 | 115 | 0.6518 | 0.7833 |
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| 0.2035 | 6.96 | 134 | 0.5667 | 0.8333 |
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| 0.2195 | 8.0 | 154 | 0.6646 | 0.8333 |
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| 0.1654 | 8.99 | 173 | 0.6294 | 0.8167 |
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| 0.1581 | 9.97 | 192 | 0.7211 | 0.7833 |
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| 0.1338 | 10.96 | 211 | 0.8129 | 0.7833 |
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| 0.1188 | 12.0 | 231 | 0.7925 | 0.8167 |
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| 0.1179 | 12.99 | 250 | 0.9588 | 0.7667 |
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| 0.1017 | 13.97 | 269 | 1.0875 | 0.7167 |
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| 0.0845 | 14.96 | 288 | 0.9355 | 0.7 |
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| 0.1109 | 16.0 | 308 | 0.9387 | 0.8167 |
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| 0.0711 | 16.99 | 327 | 1.1214 | 0.7333 |
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| 0.0884 | 17.97 | 346 | 0.9688 | 0.7667 |
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| 0.0668 | 18.96 | 365 | 1.0306 | 0.8 |
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| 0.0716 | 20.0 | 385 | 1.2653 | 0.7167 |
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| 0.0643 | 20.99 | 404 | 0.9894 | 0.7833 |
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| 0.0517 | 21.97 | 423 | 1.0439 | 0.7667 |
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| 0.0597 | 22.96 | 442 | 1.1470 | 0.7667 |
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| 0.0533 | 24.0 | 462 | 1.0848 | 0.7833 |
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| 0.0529 | 24.99 | 481 | 1.1481 | 0.75 |
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| 0.0524 | 25.97 | 500 | 1.1322 | 0.7333 |
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| 0.0525 | 26.96 | 519 | 1.1868 | 0.7333 |
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| 0.0517 | 28.0 | 539 | 1.1561 | 0.7167 |
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| 0.0309 | 28.99 | 558 | 1.0562 | 0.7833 |
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| 0.0403 | 29.97 | 577 | 1.2901 | 0.7333 |
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| 0.0392 | 30.96 | 596 | 1.1295 | 0.7667 |
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| 0.0404 | 32.0 | 616 | 1.1198 | 0.7667 |
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| 0.0381 | 32.99 | 635 | 1.2986 | 0.7167 |
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| 0.0262 | 33.97 | 654 | 1.1655 | 0.75 |
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| 0.0354 | 34.96 | 673 | 1.1223 | 0.7833 |
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| 0.0224 | 36.0 | 693 | 1.1679 | 0.7833 |
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| 0.0244 | 36.99 | 712 | 1.0999 | 0.8167 |
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| 0.0368 | 37.97 | 731 | 1.1213 | 0.7833 |
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| 0.0199 | 38.96 | 750 | 1.1003 | 0.8 |
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| 0.028 | 39.48 | 760 | 1.0989 | 0.8 |
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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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