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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dataset_model2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8797595190380761
---
<!-- 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. -->
# dataset_model2
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5350
- Accuracy: 0.8798
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1141 | 0.99 | 62 | 0.4707 | 0.8647 |
| 0.1098 | 1.99 | 124 | 0.4876 | 0.8597 |
| 0.1444 | 2.99 | 186 | 0.4651 | 0.8647 |
| 0.1088 | 3.99 | 248 | 0.5397 | 0.8527 |
| 0.1404 | 4.99 | 310 | 0.4794 | 0.8727 |
| 0.0656 | 5.99 | 372 | 0.5637 | 0.8507 |
| 0.1126 | 6.99 | 434 | 0.5318 | 0.8597 |
| 0.099 | 7.99 | 496 | 0.5522 | 0.8597 |
| 0.0501 | 8.99 | 558 | 0.5654 | 0.8667 |
| 0.0878 | 9.99 | 620 | 0.5915 | 0.8517 |
| 0.0594 | 10.99 | 682 | 0.5846 | 0.8717 |
| 0.0562 | 11.99 | 744 | 0.5191 | 0.8778 |
| 0.0554 | 12.99 | 806 | 0.5425 | 0.8717 |
| 0.0368 | 13.99 | 868 | 0.5725 | 0.8778 |
| 0.0415 | 14.99 | 930 | 0.5790 | 0.8637 |
| 0.0208 | 15.99 | 992 | 0.5319 | 0.8788 |
| 0.026 | 16.99 | 1054 | 0.5622 | 0.8677 |
| 0.0307 | 17.99 | 1116 | 0.5129 | 0.8878 |
| 0.015 | 18.99 | 1178 | 0.5508 | 0.8768 |
| 0.0263 | 19.99 | 1240 | 0.5350 | 0.8798 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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