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Fashion Images Gender Age Vit Large Patch16 224 In21k v3

This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: Loss: 0.0223 Accuracy: 0.9960

KindOtherBase modelgoogle/vit-large-patch16-224-in21kVersionRevision 325c2bdBgrade

Model source

Kind
Other
File size
1.13 GB
Base model
google/vit-large-patch16-224-in21k
Version
vRevision 325c2bd
Updated
Oct 21, 2026
Downloads
32
Source
Hugging Face

Source description

fashion-images-gender-age-vit-large-patch16-224-in21k-v3

This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0223
  • Accuracy: 0.9960

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 LossEpochStepValidation LossAccuracy
0.18681.024570.05470.9853
0.12092.049140.04010.9888
0.10273.073710.02620.9937
0.06544.098280.02230.9960
0.05425.0122850.02730.9948

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3

Sources

1 source

Model artifacts

1 artifact

pytorch_model.bin

bin · 1.13 GB · SHA-256 8561ea9f685e…9f80 · Hugging Face

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Source excerpts

3 excerpts

--- license: apache-2.0 base_model: google/vit-large-patch16-224-in21k tags: - image-classification - vision - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: fashion-images-gender-age-vit-large-patch16-224-in21k-v3 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: 0.9959630911188004 --- <!-- 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-large-patch16-224-in21k-v3 This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: - Loss: 0.0223 - Accuracy: 0.9960 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.1868 | 1.0 | 2457 | 0.0547 | 0.9853 | | 0.1209 | 2.0 | 4914 | 0.0401 | 0.9888 | | 0.1027 | 3.0 | 7371 | 0.0262 | 0.9937 | | 0.0654 | 4.0 | 9828 | 0.0223 | 0.9960 | | 0.0542 | 5.0 | 12285 | 0.0273 | 0.9948 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3

Source context: 32 downloads · 5 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age-vit-large-patch16-224-in21k-v3

Source context: 19 downloads · 5 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age-vit-large-patch16-224-in21k-v3