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--- |
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tags: |
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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: minang_food_classification |
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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: imagefolder |
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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: 0.9277777777777778 |
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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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# minang_food_classification |
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This model was trained from scratch on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7860 |
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- Accuracy: 0.9278 |
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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: 1e-06 |
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- train_batch_size: 16 |
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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: cosine_with_restarts |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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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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| 1.3423 | 1.0 | 45 | 1.3263 | 0.7889 | |
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| 1.2638 | 2.0 | 90 | 1.2436 | 0.8278 | |
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| 1.2055 | 3.0 | 135 | 1.2503 | 0.8 | |
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| 1.14 | 4.0 | 180 | 1.1486 | 0.85 | |
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| 1.0908 | 5.0 | 225 | 1.0427 | 0.8778 | |
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| 1.0258 | 6.0 | 270 | 1.0210 | 0.8333 | |
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| 0.9776 | 7.0 | 315 | 0.9694 | 0.8722 | |
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| 0.9306 | 8.0 | 360 | 0.9379 | 0.8833 | |
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| 0.8985 | 9.0 | 405 | 0.9150 | 0.8778 | |
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| 0.8624 | 10.0 | 450 | 0.8884 | 0.8611 | |
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| 0.8243 | 11.0 | 495 | 0.8118 | 0.9222 | |
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| 0.8017 | 12.0 | 540 | 0.8394 | 0.8833 | |
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| 0.797 | 13.0 | 585 | 0.7761 | 0.9056 | |
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| 0.7765 | 14.0 | 630 | 0.7891 | 0.9111 | |
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| 0.7834 | 15.0 | 675 | 0.7945 | 0.8889 | |
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| 0.7483 | 16.0 | 720 | 0.7801 | 0.9 | |
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| 0.74 | 17.0 | 765 | 0.7524 | 0.9167 | |
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| 0.7315 | 18.0 | 810 | 0.7655 | 0.9111 | |
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| 0.7468 | 19.0 | 855 | 0.7860 | 0.8833 | |
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| 0.7393 | 20.0 | 900 | 0.7900 | 0.9056 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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