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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: 0.3037 |
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- Na Accuracy: 0.7297 |
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- Ordinal Accuracy: 0.5285 |
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- Ordinal Mae: 0.6723 |
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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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| 0.4062 | 0.13 | 25 | 0.3799 | 0.6216 | 0.2395 | 0.9244 | |
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| 0.3536 | 0.27 | 50 | 0.3700 | 0.6757 | 0.3840 | 0.9067 | |
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| 0.4295 | 0.4 | 75 | 0.3405 | 0.7838 | 0.2966 | 0.8798 | |
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| 0.4114 | 0.53 | 100 | 0.3906 | 0.7297 | 0.3536 | 0.8806 | |
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| 0.3521 | 0.66 | 125 | 0.3530 | 0.8108 | 0.4259 | 0.8442 | |
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| 0.3349 | 0.8 | 150 | 0.3412 | 0.7297 | 0.4753 | 0.8016 | |
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| 0.4612 | 0.93 | 175 | 0.3639 | 0.5405 | 0.4677 | 0.7604 | |
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| 0.2424 | 1.06 | 200 | 0.3297 | 0.7027 | 0.4867 | 0.7117 | |
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| 0.2928 | 1.2 | 225 | 0.3494 | 0.6757 | 0.5285 | 0.6955 | |
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| 0.2436 | 1.33 | 250 | 0.3037 | 0.7297 | 0.5285 | 0.6723 | |
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| 0.2776 | 1.46 | 275 | 0.3366 | 0.5946 | 0.5171 | 0.6727 | |
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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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