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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: dataset_model2 |
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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: train |
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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: 0.8797595190380761 |
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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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# dataset_model2 |
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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 imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5350 |
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- Accuracy: 0.8798 |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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| 0.1141 | 0.99 | 62 | 0.4707 | 0.8647 | |
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| 0.1098 | 1.99 | 124 | 0.4876 | 0.8597 | |
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| 0.1444 | 2.99 | 186 | 0.4651 | 0.8647 | |
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| 0.1088 | 3.99 | 248 | 0.5397 | 0.8527 | |
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| 0.1404 | 4.99 | 310 | 0.4794 | 0.8727 | |
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| 0.0656 | 5.99 | 372 | 0.5637 | 0.8507 | |
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| 0.1126 | 6.99 | 434 | 0.5318 | 0.8597 | |
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| 0.099 | 7.99 | 496 | 0.5522 | 0.8597 | |
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| 0.0501 | 8.99 | 558 | 0.5654 | 0.8667 | |
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| 0.0878 | 9.99 | 620 | 0.5915 | 0.8517 | |
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| 0.0594 | 10.99 | 682 | 0.5846 | 0.8717 | |
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| 0.0562 | 11.99 | 744 | 0.5191 | 0.8778 | |
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| 0.0554 | 12.99 | 806 | 0.5425 | 0.8717 | |
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| 0.0368 | 13.99 | 868 | 0.5725 | 0.8778 | |
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| 0.0415 | 14.99 | 930 | 0.5790 | 0.8637 | |
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| 0.0208 | 15.99 | 992 | 0.5319 | 0.8788 | |
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| 0.026 | 16.99 | 1054 | 0.5622 | 0.8677 | |
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| 0.0307 | 17.99 | 1116 | 0.5129 | 0.8878 | |
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| 0.015 | 18.99 | 1178 | 0.5508 | 0.8768 | |
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| 0.0263 | 19.99 | 1240 | 0.5350 | 0.8798 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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