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Fashion Images Perspectives

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the touchtech/fashion-images-perspectives dataset. It achieves the following results on the evaluation set: Loss: 0.2280 Accuracy: 0.9269

ArtOtherBasismodellgoogle/vit-base-patch16-224-in21kVersionRevision 53bf1acBBewertung

Modellquelle

Art
Other
Dateigröße
327 MB
Basismodell
google/vit-base-patch16-224-in21k
Version
vRevision 53bf1ac
Aktualisiert
6. Okt. 2026
Downloads
7
Quelle
Hugging Face

Quellenbeschreibung

fashion-images-perspectives

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

  • Loss: 0.2280
  • Accuracy: 0.9269

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
0.56771.030420.39960.8838
0.42592.060840.39840.8747
0.34483.091260.25910.9190
0.30944.0121680.22800.9269
0.24495.0152100.25830.9229

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 53bf1ac36d255d18b8a858c50dac97a91ad2b71b
huggingface.co/touchtech/fashion-images-perspectives/tree/53bf1ac36d255d18b8a858c50dac97a91ad2b71b

Verifiziert 6. Okt.

Modellartefakte

1 Artefakt

pytorch_model.bin

bin · 327 MB · SHA-256 850b5a82dedd…d1d6 · 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-perspectives results: - task: name: Image Classification type: image-classification dataset: name: touchtech/fashion-images-perspectives type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9268747088961341 --- <!-- 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-perspectives 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-perspectives dataset. It achieves the following results on the evaluation set: - Loss: 0.2280 - Accuracy: 0.9269 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.5677 | 1.0 | 3042 | 0.3996 | 0.8838 | | 0.4259 | 2.0 | 6084 | 0.3984 | 0.8747 | | 0.3448 | 3.0 | 9126 | 0.2591 | 0.9190 | | 0.3094 | 4.0 | 12168 | 0.2280 | 0.9269 | | 0.2449 | 5.0 | 15210 | 0.2583 | 0.9229 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

Source context: 7 downloads · 1 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-perspectives

Source context: 13 downloads · 1 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-perspectives