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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- image-classification |
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- generated_from_trainer |
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model-index: |
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- name: ryan_model3272024 |
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results: [] |
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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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# ryan_model3272024 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0327 |
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- Na Accuracy: 0.956 |
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- Ordinal Accuracy: 0.568 |
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- Ordinal Mae: 56.3484 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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: 4 |
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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 | Na Accuracy | Ordinal Accuracy | Ordinal Mae | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:| |
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| 1.3578 | 0.32 | 100 | 1.2058 | 0.944 | 0.54 | 90.9846 | |
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| 1.089 | 0.64 | 200 | 1.0987 | 0.95 | 0.548 | 120.7097 | |
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| 0.924 | 0.96 | 300 | 1.0838 | 0.946 | 0.568 | 76.7982 | |
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| 0.694 | 1.28 | 400 | 1.0680 | 0.942 | 0.556 | 105.6312 | |
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| 0.7739 | 1.6 | 500 | 1.0327 | 0.956 | 0.568 | 56.3484 | |
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| 0.5935 | 1.92 | 600 | 1.0479 | 0.932 | 0.598 | 50.4520 | |
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| 0.3525 | 2.24 | 700 | 1.1915 | 0.94 | 0.578 | 68.5099 | |
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| 0.2385 | 2.56 | 800 | 1.1303 | 0.948 | 0.586 | 43.0221 | |
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| 0.3423 | 2.88 | 900 | 1.1767 | 0.94 | 0.604 | 72.1437 | |
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| 0.0674 | 3.19 | 1000 | 1.2294 | 0.938 | 0.606 | 28.0702 | |
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| 0.1206 | 3.51 | 1100 | 1.2336 | 0.938 | 0.616 | 65.0794 | |
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| 0.1261 | 3.83 | 1200 | 1.2907 | 0.938 | 0.604 | 45.8334 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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