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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-RU3-40
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8333333333333334
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-RU3-40
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.
It achieves the following results on the evaluation set:
- Loss: 0.5667
- Accuracy: 0.8333
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3821 | 0.99 | 19 | 1.3119 | 0.4833 |
| 1.2698 | 1.97 | 38 | 1.0852 | 0.6167 |
| 0.9819 | 2.96 | 57 | 0.8757 | 0.7 |
| 0.6671 | 4.0 | 77 | 0.7689 | 0.7333 |
| 0.4248 | 4.99 | 96 | 0.7294 | 0.7167 |
| 0.3005 | 5.97 | 115 | 0.6518 | 0.7833 |
| 0.2035 | 6.96 | 134 | 0.5667 | 0.8333 |
| 0.2195 | 8.0 | 154 | 0.6646 | 0.8333 |
| 0.1654 | 8.99 | 173 | 0.6294 | 0.8167 |
| 0.1581 | 9.97 | 192 | 0.7211 | 0.7833 |
| 0.1338 | 10.96 | 211 | 0.8129 | 0.7833 |
| 0.1188 | 12.0 | 231 | 0.7925 | 0.8167 |
| 0.1179 | 12.99 | 250 | 0.9588 | 0.7667 |
| 0.1017 | 13.97 | 269 | 1.0875 | 0.7167 |
| 0.0845 | 14.96 | 288 | 0.9355 | 0.7 |
| 0.1109 | 16.0 | 308 | 0.9387 | 0.8167 |
| 0.0711 | 16.99 | 327 | 1.1214 | 0.7333 |
| 0.0884 | 17.97 | 346 | 0.9688 | 0.7667 |
| 0.0668 | 18.96 | 365 | 1.0306 | 0.8 |
| 0.0716 | 20.0 | 385 | 1.2653 | 0.7167 |
| 0.0643 | 20.99 | 404 | 0.9894 | 0.7833 |
| 0.0517 | 21.97 | 423 | 1.0439 | 0.7667 |
| 0.0597 | 22.96 | 442 | 1.1470 | 0.7667 |
| 0.0533 | 24.0 | 462 | 1.0848 | 0.7833 |
| 0.0529 | 24.99 | 481 | 1.1481 | 0.75 |
| 0.0524 | 25.97 | 500 | 1.1322 | 0.7333 |
| 0.0525 | 26.96 | 519 | 1.1868 | 0.7333 |
| 0.0517 | 28.0 | 539 | 1.1561 | 0.7167 |
| 0.0309 | 28.99 | 558 | 1.0562 | 0.7833 |
| 0.0403 | 29.97 | 577 | 1.2901 | 0.7333 |
| 0.0392 | 30.96 | 596 | 1.1295 | 0.7667 |
| 0.0404 | 32.0 | 616 | 1.1198 | 0.7667 |
| 0.0381 | 32.99 | 635 | 1.2986 | 0.7167 |
| 0.0262 | 33.97 | 654 | 1.1655 | 0.75 |
| 0.0354 | 34.96 | 673 | 1.1223 | 0.7833 |
| 0.0224 | 36.0 | 693 | 1.1679 | 0.7833 |
| 0.0244 | 36.99 | 712 | 1.0999 | 0.8167 |
| 0.0368 | 37.97 | 731 | 1.1213 | 0.7833 |
| 0.0199 | 38.96 | 750 | 1.1003 | 0.8 |
| 0.028 | 39.48 | 760 | 1.0989 | 0.8 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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