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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: 0.2552 |
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- Na Accuracy: 0.95 |
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- Ordinal Accuracy: 0.6267 |
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- Ordinal Mae: 1.1586 |
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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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| 0.3853 | 0.32 | 100 | 0.3272 | 0.924 | 0.52 | 1.2106 | |
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| 0.3396 | 0.64 | 200 | 0.2741 | 0.94 | 0.5644 | 1.1640 | |
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| 0.2075 | 0.96 | 300 | 0.2772 | 0.946 | 0.5933 | 1.1942 | |
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| 0.196 | 1.28 | 400 | 0.2738 | 0.95 | 0.6133 | 1.1984 | |
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| 0.2228 | 1.6 | 500 | 0.2685 | 0.956 | 0.62 | 1.1989 | |
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| 0.1816 | 1.92 | 600 | 0.2552 | 0.95 | 0.6267 | 1.1586 | |
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| 0.0682 | 2.24 | 700 | 0.2721 | 0.952 | 0.6578 | 1.1558 | |
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| 0.0795 | 2.56 | 800 | 0.2754 | 0.948 | 0.6333 | 1.1599 | |
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| 0.1367 | 2.88 | 900 | 0.2953 | 0.946 | 0.64 | 1.1667 | |
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| 0.0387 | 3.19 | 1000 | 0.2923 | 0.944 | 0.6378 | 1.2025 | |
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| 0.0293 | 3.51 | 1100 | 0.2885 | 0.948 | 0.6644 | 1.1666 | |
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| 0.0286 | 3.83 | 1200 | 0.2868 | 0.95 | 0.6711 | 1.1626 | |
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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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