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README.md
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: attraction-classifier
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results:
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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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# 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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## Model description
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Framework versions
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- Transformers 4.31.0
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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: attraction-classifier
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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: smtn_girls_likeOrNot
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split: train
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args: smtn_girls_likeOrNot
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8284457478005866
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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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# 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: 0.4361
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- Accuracy: 0.8284
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## Model description
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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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| 0.6014 | 0.98 | 42 | 0.5286 | 0.7507 |
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| 0.4479 | 1.99 | 85 | 0.4547 | 0.8094 |
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| 0.3988 | 2.99 | 128 | 0.4259 | 0.8284 |
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| 0.3773 | 4.0 | 171 | 0.4475 | 0.7962 |
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| 0.3217 | 4.98 | 213 | 0.4155 | 0.8226 |
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| 0.2844 | 5.99 | 256 | 0.4423 | 0.8065 |
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| 0.2519 | 6.99 | 299 | 0.4961 | 0.8065 |
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| 0.2527 | 8.0 | 342 | 0.4642 | 0.8123 |
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| 0.2165 | 8.98 | 384 | 0.4860 | 0.8050 |
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| 0.2323 | 9.82 | 420 | 0.4361 | 0.8284 |
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### Framework versions
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- Transformers 4.31.0
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