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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-ve-U13b-80RX3
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: 0.9130434782608695
---
<!-- 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-ve-U13b-80RX3
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: 0.4344
- Accuracy: 0.9130
## 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: 4.74e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.33 | 0.99 | 51 | 1.3133 | 0.3478 |
| 1.0288 | 2.0 | 103 | 1.0045 | 0.5652 |
| 0.7322 | 2.99 | 154 | 0.7309 | 0.8043 |
| 0.5476 | 4.0 | 206 | 0.6316 | 0.7826 |
| 0.2863 | 4.99 | 257 | 0.5598 | 0.8043 |
| 0.3149 | 6.0 | 309 | 0.5428 | 0.8478 |
| 0.1489 | 6.99 | 360 | 0.5150 | 0.8696 |
| 0.1134 | 8.0 | 412 | 0.4585 | 0.8043 |
| 0.1613 | 8.99 | 463 | 0.6284 | 0.8478 |
| 0.1855 | 10.0 | 515 | 0.5985 | 0.8478 |
| 0.1908 | 10.99 | 566 | 1.0336 | 0.7391 |
| 0.2293 | 12.0 | 618 | 0.7746 | 0.8043 |
| 0.1414 | 12.99 | 669 | 0.6517 | 0.8261 |
| 0.0877 | 14.0 | 721 | 0.5639 | 0.8261 |
| 0.1302 | 14.99 | 772 | 0.7687 | 0.8261 |
| 0.047 | 16.0 | 824 | 0.6773 | 0.8696 |
| 0.1045 | 16.99 | 875 | 0.4344 | 0.9130 |
| 0.0751 | 18.0 | 927 | 1.0160 | 0.7391 |
| 0.1141 | 18.99 | 978 | 0.6643 | 0.8696 |
| 0.1756 | 20.0 | 1030 | 0.5582 | 0.8913 |
| 0.1212 | 20.99 | 1081 | 0.5641 | 0.8913 |
| 0.0903 | 22.0 | 1133 | 0.6990 | 0.8261 |
| 0.0693 | 22.99 | 1184 | 0.5548 | 0.8913 |
| 0.0048 | 24.0 | 1236 | 0.6958 | 0.8478 |
| 0.0785 | 24.99 | 1287 | 0.7886 | 0.8043 |
| 0.0373 | 26.0 | 1339 | 0.6345 | 0.8478 |
| 0.0763 | 26.99 | 1390 | 0.6830 | 0.8696 |
| 0.0621 | 28.0 | 1442 | 0.7294 | 0.8478 |
| 0.0367 | 28.99 | 1493 | 0.6636 | 0.8696 |
| 0.0124 | 30.0 | 1545 | 0.8031 | 0.8478 |
| 0.0759 | 30.99 | 1596 | 0.7076 | 0.8696 |
| 0.0786 | 32.0 | 1648 | 0.8024 | 0.8261 |
| 0.0487 | 32.99 | 1699 | 0.7927 | 0.8696 |
| 0.0664 | 34.0 | 1751 | 0.9607 | 0.8261 |
| 0.0054 | 34.99 | 1802 | 0.9702 | 0.8261 |
| 0.0277 | 36.0 | 1854 | 0.8351 | 0.8261 |
| 0.0025 | 36.99 | 1905 | 0.9318 | 0.8261 |
| 0.0188 | 38.0 | 1957 | 0.8995 | 0.8478 |
| 0.0385 | 38.99 | 2008 | 0.8928 | 0.8478 |
| 0.0474 | 39.61 | 2040 | 0.8863 | 0.8478 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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