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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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<!-- 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_model314_3 |
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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: 0.2783 |
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- Na Accuracy: 0.9389 |
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- Ordinal Mae: 0.8154 |
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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 Mae | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-----------:| |
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| 0.3676 | 0.05 | 100 | 0.3423 | 0.9274 | 1.1293 | |
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| 0.3329 | 0.09 | 200 | 0.3136 | 0.9314 | 1.0706 | |
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| 0.3134 | 0.14 | 300 | 0.3302 | 0.9166 | 1.1220 | |
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| 0.314 | 0.19 | 400 | 0.2992 | 0.9256 | 0.8202 | |
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| 0.2965 | 0.23 | 500 | 0.3198 | 0.9249 | 1.2210 | |
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| 0.3068 | 0.28 | 600 | 0.2673 | 0.9372 | 1.1036 | |
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| 0.2824 | 0.32 | 700 | 0.2922 | 0.9372 | 1.4977 | |
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| 0.2914 | 0.37 | 800 | 0.2798 | 0.9384 | 0.7789 | |
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| 0.2968 | 0.42 | 900 | 0.2710 | 0.9369 | 0.9694 | |
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| 0.2433 | 0.46 | 1000 | 0.2652 | 0.9372 | 1.0212 | |
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| 0.2438 | 0.51 | 1100 | 0.2783 | 0.9389 | 0.8154 | |
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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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