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--- |
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license: apache-2.0 |
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base_model: NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes |
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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: swin-tiny-patch4-window7-224-finetuned-student_six_classes-finetuned-student_six_classes |
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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: 0.83 |
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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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# swin-tiny-patch4-window7-224-finetuned-student_six_classes-finetuned-student_six_classes |
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This model is a fine-tuned version of [NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes](https://huggingface.co/NiharGupte/swin-tiny-patch4-window7-224-finetuned-student_six_classes) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4176 |
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- Accuracy: 0.83 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.9231 | 3 | 0.4943 | 0.78 | |
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| No log | 1.8462 | 6 | 0.4716 | 0.78 | |
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| No log | 2.7692 | 9 | 0.4725 | 0.81 | |
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| 0.3732 | 4.0 | 13 | 0.4678 | 0.78 | |
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| 0.3732 | 4.9231 | 16 | 0.4779 | 0.78 | |
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| 0.3732 | 5.8462 | 19 | 0.4564 | 0.79 | |
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| 0.3459 | 6.7692 | 22 | 0.4556 | 0.82 | |
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| 0.3459 | 8.0 | 26 | 0.4757 | 0.77 | |
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| 0.3459 | 8.9231 | 29 | 0.4773 | 0.77 | |
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| 0.3273 | 9.8462 | 32 | 0.4661 | 0.77 | |
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| 0.3273 | 10.7692 | 35 | 0.4518 | 0.79 | |
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| 0.3273 | 12.0 | 39 | 0.4405 | 0.81 | |
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| 0.2974 | 12.9231 | 42 | 0.4359 | 0.82 | |
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| 0.2974 | 13.8462 | 45 | 0.4298 | 0.82 | |
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| 0.2974 | 14.7692 | 48 | 0.4242 | 0.84 | |
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| 0.2874 | 16.0 | 52 | 0.4199 | 0.84 | |
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| 0.2874 | 16.9231 | 55 | 0.4185 | 0.83 | |
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| 0.2874 | 17.8462 | 58 | 0.4179 | 0.83 | |
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| 0.2737 | 18.4615 | 60 | 0.4176 | 0.83 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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