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Fashion Images Gender Age

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: Loss: 0.0244 Accuracy: 0.9942

ArtOtherBasismodellgoogle/vit-base-patch16-224-in21kVersionRevision 89f032cBBewertung

Modellquelle

Art
Other
Dateigröße
327 MB
Basismodell
google/vit-base-patch16-224-in21k
Version
vRevision 89f032c
Aktualisiert
6. Okt. 2026
Downloads
27
Quelle
Hugging Face

Quellenbeschreibung

fashion-images-gender-age

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

  • Loss: 0.0244
  • Accuracy: 0.9942

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
0.1671.024220.07960.9781
0.11692.048440.04800.9883
0.09933.072660.02640.9936
0.07384.096880.02440.9942
0.04975.0121100.02970.9921

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3

Quellen

1 Quelle
Hugging FacePrimärVersion 89f032c408878f1d0d044fe48ffa2c3a7ebd3658
huggingface.co/touchtech/fashion-images-gender-age/tree/89f032c408878f1d0d044fe48ffa2c3a7ebd3658

Verifiziert 6. Okt.

Modellartefakte

1 Artefakt

pytorch_model.bin

bin · 327 MB · SHA-256 359a967060e8…dcfe · Hugging Face

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Quellenauszüge

3 Auszüge

--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - image-classification - vision - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: fashion-images-gender-age 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: 0.9941520467836257 --- <!-- 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 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 touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: - Loss: 0.0244 - Accuracy: 0.9942 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.167 | 1.0 | 2422 | 0.0796 | 0.9781 | | 0.1169 | 2.0 | 4844 | 0.0480 | 0.9883 | | 0.0993 | 3.0 | 7266 | 0.0264 | 0.9936 | | 0.0738 | 4.0 | 9688 | 0.0244 | 0.9942 | | 0.0497 | 5.0 | 12110 | 0.0297 | 0.9921 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

Source context: 27 downloads · 4 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age

Source context: 17 downloads · 4 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-gender-age