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README.md ADDED
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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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+ - generated_from_trainer
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+ model-index:
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+ - name: ryan_model314_3
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+ results: []
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+ ---
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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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+
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+ # ryan_model314_3
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+
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2818
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+ - Na Accuracy: 0.955
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+ - Ordinal Mae: 1.2378
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Mae |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-----------:|
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+ | 0.4505 | 0.2 | 25 | 0.4262 | 0.9 | 1.0092 |
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+ | 0.3847 | 0.4 | 50 | 0.3676 | 0.935 | 1.3719 |
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+ | 0.3061 | 0.6 | 75 | 0.3262 | 0.945 | 0.7486 |
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+ | 0.2744 | 0.8 | 100 | 0.3524 | 0.905 | 1.1408 |
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+ | 0.2384 | 1.0 | 125 | 0.3611 | 0.93 | 0.6747 |
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+ | 0.2021 | 1.2 | 150 | 0.3105 | 0.95 | 1.0441 |
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+ | 0.2234 | 1.4 | 175 | 0.2738 | 0.955 | 1.4168 |
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+ | 0.187 | 1.6 | 200 | 0.2688 | 0.955 | 1.3653 |
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+ | 0.2008 | 1.8 | 225 | 0.2669 | 0.96 | 0.8936 |
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+ | 0.1541 | 2.0 | 250 | 0.2547 | 0.95 | 1.2090 |
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+ | 0.1201 | 2.2 | 275 | 0.2725 | 0.95 | 0.7955 |
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+ | 0.113 | 2.4 | 300 | 0.2818 | 0.955 | 1.2378 |
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+
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+
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+ ### Framework versions
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+
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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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