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--- |
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license: apache-2.0 |
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base_model: facebook/deit-tiny-patch16-224 |
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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: smids_10x_deit_tiny_sgd_0001_fold1 |
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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: test |
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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: 0.8113522537562604 |
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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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# smids_10x_deit_tiny_sgd_0001_fold1 |
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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: 0.4530 |
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- Accuracy: 0.8114 |
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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: 32 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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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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| 1.0181 | 1.0 | 751 | 0.9693 | 0.5359 | |
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| 0.81 | 2.0 | 1502 | 0.8850 | 0.5993 | |
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| 0.7699 | 3.0 | 2253 | 0.8246 | 0.6377 | |
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| 0.6601 | 4.0 | 3004 | 0.7789 | 0.6578 | |
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| 0.653 | 5.0 | 3755 | 0.7391 | 0.6745 | |
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| 0.6463 | 6.0 | 4506 | 0.7047 | 0.6912 | |
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| 0.5744 | 7.0 | 5257 | 0.6756 | 0.7028 | |
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| 0.4963 | 8.0 | 6008 | 0.6490 | 0.7129 | |
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| 0.5329 | 9.0 | 6759 | 0.6286 | 0.7195 | |
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| 0.5165 | 10.0 | 7510 | 0.6094 | 0.7295 | |
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| 0.5717 | 11.0 | 8261 | 0.5949 | 0.7279 | |
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| 0.4844 | 12.0 | 9012 | 0.5809 | 0.7396 | |
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| 0.4587 | 13.0 | 9763 | 0.5699 | 0.7446 | |
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| 0.4195 | 14.0 | 10514 | 0.5589 | 0.7496 | |
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| 0.4521 | 15.0 | 11265 | 0.5504 | 0.7579 | |
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| 0.4327 | 16.0 | 12016 | 0.5411 | 0.7596 | |
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| 0.4611 | 17.0 | 12767 | 0.5341 | 0.7663 | |
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| 0.4248 | 18.0 | 13518 | 0.5294 | 0.7746 | |
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| 0.4694 | 19.0 | 14269 | 0.5215 | 0.7780 | |
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| 0.395 | 20.0 | 15020 | 0.5170 | 0.7880 | |
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| 0.3437 | 21.0 | 15771 | 0.5117 | 0.7880 | |
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| 0.4367 | 22.0 | 16522 | 0.5057 | 0.7947 | |
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| 0.3451 | 23.0 | 17273 | 0.5010 | 0.7930 | |
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| 0.4413 | 24.0 | 18024 | 0.4962 | 0.7930 | |
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| 0.3908 | 25.0 | 18775 | 0.4929 | 0.7930 | |
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| 0.4631 | 26.0 | 19526 | 0.4899 | 0.7930 | |
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| 0.3779 | 27.0 | 20277 | 0.4860 | 0.7930 | |
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| 0.4436 | 28.0 | 21028 | 0.4829 | 0.7963 | |
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| 0.3794 | 29.0 | 21779 | 0.4792 | 0.7997 | |
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| 0.3732 | 30.0 | 22530 | 0.4775 | 0.7963 | |
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| 0.3411 | 31.0 | 23281 | 0.4746 | 0.7980 | |
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| 0.4745 | 32.0 | 24032 | 0.4718 | 0.7980 | |
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| 0.4263 | 33.0 | 24783 | 0.4692 | 0.7997 | |
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| 0.3711 | 34.0 | 25534 | 0.4676 | 0.8030 | |
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| 0.3951 | 35.0 | 26285 | 0.4656 | 0.8047 | |
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| 0.4026 | 36.0 | 27036 | 0.4635 | 0.8047 | |
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| 0.4811 | 37.0 | 27787 | 0.4621 | 0.8063 | |
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| 0.3816 | 38.0 | 28538 | 0.4609 | 0.8063 | |
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| 0.2904 | 39.0 | 29289 | 0.4596 | 0.8047 | |
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| 0.4708 | 40.0 | 30040 | 0.4586 | 0.8097 | |
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| 0.3633 | 41.0 | 30791 | 0.4575 | 0.8080 | |
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| 0.367 | 42.0 | 31542 | 0.4565 | 0.8080 | |
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| 0.4048 | 43.0 | 32293 | 0.4557 | 0.8080 | |
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| 0.3531 | 44.0 | 33044 | 0.4549 | 0.8080 | |
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| 0.3608 | 45.0 | 33795 | 0.4542 | 0.8097 | |
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| 0.3794 | 46.0 | 34546 | 0.4538 | 0.8097 | |
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| 0.3429 | 47.0 | 35297 | 0.4534 | 0.8114 | |
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| 0.395 | 48.0 | 36048 | 0.4532 | 0.8114 | |
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| 0.3682 | 49.0 | 36799 | 0.4531 | 0.8114 | |
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| 0.3927 | 50.0 | 37550 | 0.4530 | 0.8114 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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