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--- |
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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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- image-classification |
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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: vit-base-25ep |
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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: vuongnhathien/30VNFoods |
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type: imagefolder |
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config: default |
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split: validation |
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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: 0.8486111111111111 |
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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-25ep |
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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 the vuongnhathien/30VNFoods dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5506 |
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- Accuracy: 0.8486 |
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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: 0.0003 |
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- train_batch_size: 64 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 25 |
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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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| 0.6167 | 1.0 | 275 | 0.5712 | 0.8354 | |
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| 0.3183 | 2.0 | 550 | 0.5564 | 0.8406 | |
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| 0.1729 | 3.0 | 825 | 0.5955 | 0.8433 | |
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| 0.139 | 4.0 | 1100 | 0.6453 | 0.8406 | |
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| 0.0775 | 5.0 | 1375 | 0.6044 | 0.8517 | |
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| 0.0784 | 6.0 | 1650 | 0.7265 | 0.8414 | |
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| 0.0502 | 7.0 | 1925 | 0.6977 | 0.8533 | |
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| 0.0525 | 8.0 | 2200 | 0.7100 | 0.8549 | |
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| 0.0311 | 9.0 | 2475 | 0.7423 | 0.8525 | |
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| 0.026 | 10.0 | 2750 | 0.7901 | 0.8461 | |
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| 0.0183 | 11.0 | 3025 | 0.7261 | 0.8592 | |
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| 0.0218 | 12.0 | 3300 | 0.8014 | 0.8485 | |
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| 0.0135 | 13.0 | 3575 | 0.7391 | 0.8584 | |
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| 0.0066 | 14.0 | 3850 | 0.6938 | 0.8740 | |
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| 0.0047 | 15.0 | 4125 | 0.6765 | 0.8815 | |
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| 0.0052 | 16.0 | 4400 | 0.6611 | 0.8839 | |
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| 0.0033 | 17.0 | 4675 | 0.6794 | 0.8803 | |
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| 0.0037 | 18.0 | 4950 | 0.6724 | 0.8811 | |
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| 0.0026 | 19.0 | 5225 | 0.6759 | 0.8875 | |
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| 0.0031 | 20.0 | 5500 | 0.6699 | 0.8855 | |
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| 0.0028 | 21.0 | 5775 | 0.6720 | 0.8847 | |
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| 0.0029 | 22.0 | 6050 | 0.6746 | 0.8843 | |
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| 0.0016 | 23.0 | 6325 | 0.6731 | 0.8859 | |
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| 0.0016 | 24.0 | 6600 | 0.6759 | 0.8859 | |
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| 0.0019 | 25.0 | 6875 | 0.6767 | 0.8847 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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