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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-large |
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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: aesthetics_v2 |
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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: 0.5580614847630554 |
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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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# aesthetics_v2 |
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This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6501 |
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- Accuracy: 0.5581 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 3 |
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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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| 1.1465 | 0.17 | 20 | 1.6860 | 0.5313 | |
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| 1.2703 | 0.34 | 40 | 1.8412 | 0.5014 | |
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| 1.3152 | 0.52 | 60 | 1.8200 | 0.5042 | |
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| 1.2313 | 0.69 | 80 | 1.7971 | 0.5112 | |
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| 1.3476 | 0.86 | 100 | 1.7649 | 0.5100 | |
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| 1.2597 | 1.03 | 120 | 1.7454 | 0.5175 | |
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| 1.0094 | 1.2 | 140 | 1.7356 | 0.5257 | |
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| 0.9743 | 1.37 | 160 | 1.7074 | 0.5352 | |
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| 1.0209 | 1.55 | 180 | 1.7331 | 0.5322 | |
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| 1.0692 | 1.72 | 200 | 1.7370 | 0.5331 | |
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| 1.0556 | 1.89 | 220 | 1.6788 | 0.5487 | |
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| 0.8634 | 2.06 | 240 | 1.6644 | 0.5536 | |
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| 0.79 | 2.23 | 260 | 1.6848 | 0.5531 | |
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| 0.7916 | 2.4 | 280 | 1.6761 | 0.5528 | |
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| 0.7454 | 2.58 | 300 | 1.6520 | 0.5534 | |
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| 0.7497 | 2.75 | 320 | 1.6337 | 0.5554 | |
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| 0.7537 | 2.92 | 340 | 1.6501 | 0.5581 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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