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deit-tiny-patch16-224-finetuned-main-gpu-20e-final

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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: deit-tiny-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: 0.9856292517006803
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+ ---
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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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+
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+ # deit-tiny-patch16-224-finetuned-main-gpu-20e-final
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0420
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+ - Accuracy: 0.9856
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.6047 | 1.0 | 551 | 0.6283 | 0.7111 |
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+ | 0.431 | 2.0 | 1102 | 0.3962 | 0.8366 |
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+ | 0.352 | 3.0 | 1653 | 0.2620 | 0.8953 |
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+ | 0.2682 | 4.0 | 2204 | 0.1814 | 0.9318 |
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+ | 0.2533 | 5.0 | 2755 | 0.1564 | 0.9396 |
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+ | 0.2069 | 6.0 | 3306 | 0.1243 | 0.9531 |
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+ | 0.2065 | 7.0 | 3857 | 0.1048 | 0.9603 |
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+ | 0.194 | 8.0 | 4408 | 0.1019 | 0.9636 |
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+ | 0.1879 | 9.0 | 4959 | 0.0877 | 0.9671 |
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+ | 0.1584 | 10.0 | 5510 | 0.0870 | 0.9687 |
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+ | 0.1426 | 11.0 | 6061 | 0.0814 | 0.9718 |
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+ | 0.1596 | 12.0 | 6612 | 0.0740 | 0.9749 |
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+ | 0.1125 | 13.0 | 7163 | 0.0613 | 0.9781 |
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+ | 0.1374 | 14.0 | 7714 | 0.0570 | 0.9787 |
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+ | 0.1003 | 15.0 | 8265 | 0.0596 | 0.9793 |
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+ | 0.109 | 16.0 | 8816 | 0.0511 | 0.9815 |
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+ | 0.1206 | 17.0 | 9367 | 0.0497 | 0.9829 |
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+ | 0.1024 | 18.0 | 9918 | 0.0437 | 0.9844 |
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+ | 0.1051 | 19.0 | 10469 | 0.0420 | 0.9851 |
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+ | 0.0955 | 20.0 | 11020 | 0.0420 | 0.9856 |
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+
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+
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+ ### Framework versions
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+
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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