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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-U8-40
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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: 0.8666666666666667
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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-U8-40
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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: 0.5495
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- Accuracy: 0.8667
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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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| 1.3457 | 1.0 | 20 | 1.3128 | 0.45 |
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| 1.1498 | 2.0 | 40 | 1.1047 | 0.5667 |
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| 0.8312 | 3.0 | 60 | 0.8231 | 0.65 |
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| 0.5334 | 4.0 | 80 | 0.5719 | 0.8167 |
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| 0.3582 | 5.0 | 100 | 0.5495 | 0.8667 |
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| 0.2389 | 6.0 | 120 | 0.5801 | 0.8333 |
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| 0.2055 | 7.0 | 140 | 0.6727 | 0.8167 |
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| 0.1738 | 8.0 | 160 | 0.7238 | 0.8 |
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| 0.1556 | 9.0 | 180 | 0.7665 | 0.75 |
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| 0.1461 | 10.0 | 200 | 0.8229 | 0.7667 |
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| 0.1401 | 11.0 | 220 | 0.8102 | 0.75 |
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| 0.08 | 12.0 | 240 | 0.6609 | 0.8333 |
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| 0.0989 | 13.0 | 260 | 0.6703 | 0.8333 |
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| 0.0773 | 14.0 | 280 | 0.7303 | 0.8167 |
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| 0.089 | 15.0 | 300 | 0.7757 | 0.7833 |
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| 0.11 | 16.0 | 320 | 0.7279 | 0.8 |
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| 0.086 | 17.0 | 340 | 0.8491 | 0.7833 |
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| 0.0671 | 18.0 | 360 | 0.7950 | 0.8 |
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| 0.0775 | 19.0 | 380 | 0.6753 | 0.85 |
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| 0.0636 | 20.0 | 400 | 0.7881 | 0.8333 |
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| 0.0737 | 21.0 | 420 | 0.7450 | 0.8333 |
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| 0.0583 | 22.0 | 440 | 0.8295 | 0.8 |
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| 0.0646 | 23.0 | 460 | 0.8227 | 0.8333 |
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| 0.0637 | 24.0 | 480 | 0.9030 | 0.7833 |
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| 0.0647 | 25.0 | 500 | 0.8656 | 0.8 |
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| 0.0477 | 26.0 | 520 | 0.8362 | 0.8 |
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| 0.0481 | 27.0 | 540 | 0.8389 | 0.8 |
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| 0.0355 | 28.0 | 560 | 0.9424 | 0.8 |
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| 0.0352 | 29.0 | 580 | 0.8963 | 0.8 |
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| 0.0335 | 30.0 | 600 | 0.8560 | 0.8333 |
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| 0.0372 | 31.0 | 620 | 0.7250 | 0.8333 |
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| 0.0389 | 32.0 | 640 | 0.7846 | 0.8167 |
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| 0.0425 | 33.0 | 660 | 0.8532 | 0.8333 |
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| 0.0404 | 34.0 | 680 | 0.8169 | 0.8333 |
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| 0.0359 | 35.0 | 700 | 0.8682 | 0.8167 |
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| 0.0231 | 36.0 | 720 | 0.9362 | 0.8167 |
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| 0.027 | 37.0 | 740 | 0.9139 | 0.8167 |
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| 0.0214 | 38.0 | 760 | 0.8782 | 0.8167 |
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| 0.0191 | 39.0 | 780 | 0.8794 | 0.8167 |
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| 0.0293 | 40.0 | 800 | 0.8929 | 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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