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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: hushem_conflu_deneme_fold5 |
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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: 0.6341463414634146 |
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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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# hushem_conflu_deneme_fold5 |
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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: 1.9630 |
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- Accuracy: 0.6341 |
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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: 0.001 |
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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: 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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| No log | 1.0 | 6 | 1.4708 | 0.2439 | |
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| 1.7951 | 2.0 | 12 | 1.3099 | 0.2439 | |
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| 1.7951 | 3.0 | 18 | 1.1130 | 0.4146 | |
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| 1.2772 | 4.0 | 24 | 1.0471 | 0.7073 | |
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| 1.1124 | 5.0 | 30 | 1.2680 | 0.5366 | |
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| 1.1124 | 6.0 | 36 | 1.0908 | 0.5122 | |
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| 0.9481 | 7.0 | 42 | 1.5674 | 0.3902 | |
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| 0.9481 | 8.0 | 48 | 0.8947 | 0.6098 | |
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| 0.9653 | 9.0 | 54 | 1.1885 | 0.6098 | |
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| 0.639 | 10.0 | 60 | 0.9898 | 0.6585 | |
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| 0.639 | 11.0 | 66 | 1.7943 | 0.4634 | |
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| 0.5108 | 12.0 | 72 | 1.7088 | 0.5366 | |
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| 0.5108 | 13.0 | 78 | 1.6432 | 0.5610 | |
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| 0.1679 | 14.0 | 84 | 1.5598 | 0.5854 | |
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| 0.1286 | 15.0 | 90 | 2.1600 | 0.5854 | |
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| 0.1286 | 16.0 | 96 | 1.9849 | 0.5854 | |
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| 0.0501 | 17.0 | 102 | 1.9630 | 0.6341 | |
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| 0.0501 | 18.0 | 108 | 1.9630 | 0.6341 | |
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| 0.0271 | 19.0 | 114 | 1.9630 | 0.6341 | |
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| 0.0437 | 20.0 | 120 | 1.9630 | 0.6341 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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