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---
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit
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: 0.9985885673959068
---
<!-- 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
This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0048
- Accuracy: 0.9986
## 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: 2e-05
- train_batch_size: 24
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2323 | 1.0 | 1595 | 0.0450 | 0.9859 |
| 0.095 | 2.0 | 3190 | 0.0332 | 0.9889 |
| 0.0648 | 3.0 | 4785 | 0.0256 | 0.9922 |
| 0.0568 | 4.0 | 6380 | 0.0145 | 0.9958 |
| 0.0493 | 5.0 | 7975 | 0.0248 | 0.9915 |
| 0.042 | 6.0 | 9570 | 0.0195 | 0.9939 |
| 0.0383 | 7.0 | 11165 | 0.0087 | 0.9969 |
| 0.0345 | 8.0 | 12760 | 0.0143 | 0.9960 |
| 0.0285 | 9.0 | 14355 | 0.0115 | 0.9972 |
| 0.0257 | 10.0 | 15950 | 0.0131 | 0.9965 |
| 0.0248 | 11.0 | 17545 | 0.0068 | 0.9979 |
| 0.0235 | 12.0 | 19140 | 0.0065 | 0.9979 |
| 0.0201 | 13.0 | 20735 | 0.0056 | 0.9976 |
| 0.0161 | 14.0 | 22330 | 0.0033 | 0.9988 |
| 0.017 | 15.0 | 23925 | 0.0041 | 0.9988 |
| 0.0144 | 16.0 | 25520 | 0.0032 | 0.9993 |
| 0.0121 | 17.0 | 27115 | 0.0055 | 0.9979 |
| 0.0105 | 18.0 | 28710 | 0.0052 | 0.9984 |
| 0.0103 | 19.0 | 30305 | 0.0054 | 0.9984 |
| 0.0092 | 20.0 | 31900 | 0.0048 | 0.9986 |
### Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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