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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: 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: 0.8286558345642541 |
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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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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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