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README.md
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metrics:
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- accuracy
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model-index:
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results:
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name: Image Classification
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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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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) 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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### Framework versions
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metrics:
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- accuracy
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model-index:
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- name: attraction-classifier
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results:
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- task:
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name: Image Classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8286558345642541
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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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# attraction-classifier
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3887
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- Accuracy: 0.8287
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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: 10
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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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| 0.5824 | 0.99 | 42 | 0.5195 | 0.7829 |
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| 0.4574 | 2.0 | 85 | 0.4473 | 0.8154 |
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| 0.4165 | 2.99 | 127 | 0.3977 | 0.8316 |
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| 0.346 | 4.0 | 170 | 0.3881 | 0.8390 |
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| 0.3025 | 4.99 | 212 | 0.3950 | 0.8213 |
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| 0.3085 | 6.0 | 255 | 0.3965 | 0.8139 |
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| 0.2646 | 6.99 | 297 | 0.3895 | 0.8552 |
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| 0.3022 | 8.0 | 340 | 0.3828 | 0.8390 |
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| 0.2384 | 8.99 | 382 | 0.3878 | 0.8375 |
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| 0.2162 | 9.88 | 420 | 0.3887 | 0.8287 |
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### Framework versions
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