Model save
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1](https://huggingface.co/Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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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:
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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 | 0.92 | 3 | 0.
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| No log | 1.85 | 6 | 0.
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| No log | 2.77 | 9 | 0.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8444444444444444
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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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This model is a fine-tuned version of [Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1](https://huggingface.co/Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp1) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3494
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- Accuracy: 0.8444
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## Model description
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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: 30
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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 | 0.92 | 3 | 0.4305 | 0.8222 |
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| No log | 1.85 | 6 | 0.4510 | 0.8 |
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| No log | 2.77 | 9 | 0.4329 | 0.7778 |
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| 0.3489 | 4.0 | 13 | 0.4965 | 0.7778 |
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| 0.3489 | 4.92 | 16 | 0.4247 | 0.8 |
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| 0.3489 | 5.85 | 19 | 0.3559 | 0.8444 |
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| 0.2872 | 6.77 | 22 | 0.3628 | 0.8667 |
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| 0.2872 | 8.0 | 26 | 0.3511 | 0.8667 |
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| 0.2872 | 8.92 | 29 | 0.3538 | 0.8667 |
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| 0.3071 | 9.85 | 32 | 0.3644 | 0.8222 |
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| 0.3071 | 10.77 | 35 | 0.3860 | 0.8222 |
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| 0.3071 | 12.0 | 39 | 0.5917 | 0.8 |
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| 0.2765 | 12.92 | 42 | 0.5149 | 0.7778 |
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| 0.2765 | 13.85 | 45 | 0.5605 | 0.7556 |
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| 0.2765 | 14.77 | 48 | 0.4737 | 0.8 |
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| 0.2637 | 16.0 | 52 | 0.4109 | 0.8444 |
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| 0.2637 | 16.92 | 55 | 0.3584 | 0.8222 |
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| 0.2637 | 17.85 | 58 | 0.3771 | 0.8222 |
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| 0.2082 | 18.77 | 61 | 0.4406 | 0.8222 |
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| 0.2082 | 20.0 | 65 | 0.3592 | 0.8222 |
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| 0.2082 | 20.92 | 68 | 0.3302 | 0.8667 |
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| 0.1944 | 21.85 | 71 | 0.3206 | 0.8444 |
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| 0.1944 | 22.77 | 74 | 0.3215 | 0.8667 |
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| 0.1944 | 24.0 | 78 | 0.3209 | 0.8667 |
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| 0.2144 | 24.92 | 81 | 0.3327 | 0.8444 |
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| 0.2144 | 25.85 | 84 | 0.3506 | 0.8444 |
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| 0.2144 | 26.77 | 87 | 0.3545 | 0.8444 |
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| 0.1754 | 27.69 | 90 | 0.3494 | 0.8444 |
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### Framework versions
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model.safetensors
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