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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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widget: |
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- url: img_test.jpeg |
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example_title: Takoyaki |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-patch16-224-finetuned-food101 |
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results: [] |
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datasets: |
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- ethz/food101 |
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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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# vit-base-patch16-224-finetuned-food101 |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on Food-101 Dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6401 |
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- Accuracy: 0.8350 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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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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| 0.912 | 0.9986 | 532 | 0.8397 | 0.7968 | |
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| 0.7233 | 1.9991 | 1065 | 0.6781 | 0.8294 | |
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| 0.6047 | 2.9958 | 1596 | 0.6401 | 0.8350 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
