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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-patch16-224-finetuned-main-gpu-20e-final |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9909863945578231 |
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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-patch16-224-finetuned-main-gpu-20e-final |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0285 |
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- Accuracy: 0.9910 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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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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| 0.4852 | 1.0 | 551 | 0.4533 | 0.8042 | |
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| 0.3033 | 2.0 | 1102 | 0.2157 | 0.9157 | |
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| 0.2339 | 3.0 | 1653 | 0.1212 | 0.9534 | |
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| 0.1694 | 4.0 | 2204 | 0.1076 | 0.9603 | |
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| 0.1715 | 5.0 | 2755 | 0.0830 | 0.9692 | |
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| 0.1339 | 6.0 | 3306 | 0.0674 | 0.9762 | |
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| 0.1527 | 7.0 | 3857 | 0.0556 | 0.9791 | |
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| 0.1214 | 8.0 | 4408 | 0.0455 | 0.9832 | |
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| 0.1062 | 9.0 | 4959 | 0.0466 | 0.9829 | |
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| 0.0974 | 10.0 | 5510 | 0.0403 | 0.9849 | |
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| 0.0875 | 11.0 | 6061 | 0.0385 | 0.9860 | |
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| 0.0992 | 12.0 | 6612 | 0.0376 | 0.9870 | |
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| 0.065 | 13.0 | 7163 | 0.0392 | 0.9864 | |
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| 0.0775 | 14.0 | 7714 | 0.0344 | 0.9890 | |
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| 0.0544 | 15.0 | 8265 | 0.0362 | 0.9888 | |
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| 0.0584 | 16.0 | 8816 | 0.0422 | 0.9872 | |
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| 0.0722 | 17.0 | 9367 | 0.0314 | 0.9900 | |
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| 0.0765 | 18.0 | 9918 | 0.0313 | 0.9908 | |
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| 0.0696 | 19.0 | 10469 | 0.0297 | 0.9912 | |
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| 0.0596 | 20.0 | 11020 | 0.0285 | 0.9910 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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