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Fashion Images Perspectives 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-perspectives dataset. It achieves the following results on the evaluation set: Loss: 0.2419 Accuracy: 0.9246

KindOtherBase modelgoogle/vit-large-patch16-224-in21kVersionRevision 4412effBgrade

Model source

Kind
Other
File size
1.13 GB
Base model
google/vit-large-patch16-224-in21k
Version
vRevision 4412eff
Updated
Oct 6, 2026
Downloads
5
Source
Hugging Face

Source description

fashion-images-perspectives-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-perspectives dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2419
  • Accuracy: 0.9246

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
0.43531.030700.33950.8812
0.34152.061400.25440.9192
0.26893.092100.24190.9246
0.25254.0122800.29530.9192
0.19775.0153500.24440.9356

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 3326c114fb23…5093 · 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-perspectives-vit-large-patch16-224-in21k-v3 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: 0.92455006922012 --- <!-- 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-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-perspectives dataset. It achieves the following results on the evaluation set: - Loss: 0.2419 - Accuracy: 0.9246 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.4353 | 1.0 | 3070 | 0.3395 | 0.8812 | | 0.3415 | 2.0 | 6140 | 0.2544 | 0.9192 | | 0.2689 | 3.0 | 9210 | 0.2419 | 0.9246 | | 0.2525 | 4.0 | 12280 | 0.2953 | 0.9192 | | 0.1977 | 5.0 | 15350 | 0.2444 | 0.9356 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3

Source context: 5 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-perspectives-vit-large-patch16-224-in21k-v3

Source context: 2 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo touchtech/fashion-images-perspectives-vit-large-patch16-224-in21k-v3