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--- |
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license: apache-2.0 |
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base_model: google/vit-large-patch16-224-in21k |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: fashion-images-perspectives-vit-large-patch16-224-in21k-v3 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: touchtech/fashion-images-perspectives |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.92455006922012 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# fashion-images-perspectives-vit-large-patch16-224-in21k-v3 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2419 |
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- Accuracy: 0.9246 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.4353 | 1.0 | 3070 | 0.3395 | 0.8812 | |
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| 0.3415 | 2.0 | 6140 | 0.2544 | 0.9192 | |
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| 0.2689 | 3.0 | 9210 | 0.2419 | 0.9246 | |
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| 0.2525 | 4.0 | 12280 | 0.2953 | 0.9192 | |
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| 0.1977 | 5.0 | 15350 | 0.2444 | 0.9356 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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