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---
license: apache-2.0
base_model: google/vit-huge-patch14-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: fashion-images-gender-age-vit-huge-patch14-224-in21k
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: touchtech/fashion-images-gender-age
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9894736842105263
---
<!-- 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. -->
# fashion-images-gender-age-vit-huge-patch14-224-in21k
This model is a fine-tuned version of [google/vit-huge-patch14-224-in21k](https://huggingface.co/google/vit-huge-patch14-224-in21k) on the touchtech/fashion-images-gender-age dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0346
- Accuracy: 0.9895
## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1848 | 1.0 | 2422 | 0.0777 | 0.9798 |
| 0.1055 | 2.0 | 4844 | 0.0708 | 0.9819 |
| 0.0949 | 3.0 | 7266 | 0.0440 | 0.9877 |
| 0.08 | 4.0 | 9688 | 0.0373 | 0.9883 |
| 0.063 | 5.0 | 12110 | 0.0346 | 0.9895 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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