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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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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-beans-demo-v5 |
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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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# vit-base-beans-demo-v5 |
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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 bact dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0612 |
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- Accuracy: 0.9874 |
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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: 5e-05 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.0007 | 0.17 | 100 | 0.1211 | 0.9748 | |
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| 0.0005 | 0.34 | 200 | 0.1027 | 0.9786 | |
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| 0.0195 | 0.5 | 300 | 0.0869 | 0.9836 | |
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| 0.0025 | 0.67 | 400 | 0.0823 | 0.9845 | |
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| 0.0154 | 0.84 | 500 | 0.0888 | 0.9828 | |
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| 0.0004 | 1.01 | 600 | 0.0781 | 0.9853 | |
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| 0.0004 | 1.17 | 700 | 0.0931 | 0.9832 | |
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| 0.0004 | 1.34 | 800 | 0.0995 | 0.9811 | |
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| 0.0004 | 1.51 | 900 | 0.0925 | 0.9832 | |
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| 0.0003 | 1.68 | 1000 | 0.0857 | 0.9836 | |
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| 0.0364 | 1.85 | 1100 | 0.0788 | 0.9845 | |
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| 0.0003 | 2.01 | 1200 | 0.0775 | 0.9840 | |
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| 0.0003 | 2.18 | 1300 | 0.0718 | 0.9857 | |
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| 0.0003 | 2.35 | 1400 | 0.0804 | 0.9849 | |
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| 0.0003 | 2.52 | 1500 | 0.0751 | 0.9836 | |
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| 0.0003 | 2.68 | 1600 | 0.0659 | 0.9870 | |
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| 0.0002 | 2.85 | 1700 | 0.0612 | 0.9874 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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