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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-large-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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: vit_4090_downsample_normal_da |
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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: 0.35706727135298566 |
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- name: Precision |
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type: precision |
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value: 0.426496961448031 |
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- name: Recall |
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type: recall |
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value: 0.35706727135298566 |
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- name: F1 |
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type: f1 |
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value: 0.30112832284646396 |
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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_4090_downsample_normal_da |
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This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.3528 |
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- Accuracy: 0.3571 |
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- Precision: 0.4265 |
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- Recall: 0.3571 |
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- F1: 0.3011 |
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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: 24 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.1307 | 1.0 | 1834 | 4.1849 | 0.3710 | 0.4442 | 0.3710 | 0.3346 | |
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| 0.0388 | 2.0 | 3668 | 4.7670 | 0.3805 | 0.4413 | 0.3805 | 0.3444 | |
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| 0.0277 | 3.0 | 5502 | 4.5994 | 0.4204 | 0.4645 | 0.4204 | 0.3922 | |
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| 0.0174 | 4.0 | 7336 | 4.7754 | 0.3619 | 0.4226 | 0.3619 | 0.3361 | |
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| 0.0113 | 5.0 | 9170 | 5.1718 | 0.3586 | 0.4126 | 0.3586 | 0.3005 | |
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| 0.0092 | 6.0 | 11004 | 4.9205 | 0.3800 | 0.4535 | 0.3800 | 0.3450 | |
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| 0.005 | 7.0 | 12838 | 5.8665 | 0.3701 | 0.3679 | 0.3701 | 0.2726 | |
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| 0.0033 | 8.0 | 14672 | 5.8658 | 0.3382 | 0.4145 | 0.3382 | 0.3009 | |
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| 0.001 | 9.0 | 16506 | 6.1933 | 0.3495 | 0.3938 | 0.3495 | 0.2864 | |
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| 0.0001 | 10.0 | 18340 | 6.3528 | 0.3571 | 0.4265 | 0.3571 | 0.3011 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.1 |
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