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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/dinov2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: dinov2-base_rice-leaf-disease-augmented-v2_fft |
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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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should probably proofread and complete it, then remove this comment. --> |
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# dinov2-base_rice-leaf-disease-augmented-v2_fft |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6772 |
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- Accuracy: 0.9018 |
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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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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 0.8654 | 1.0 | 125 | 0.4470 | 0.8661 | |
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| 0.2009 | 2.0 | 250 | 0.5260 | 0.8631 | |
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| 0.1148 | 3.0 | 375 | 0.6247 | 0.8690 | |
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| 0.0412 | 4.0 | 500 | 0.5468 | 0.8988 | |
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| 0.0052 | 5.0 | 625 | 0.5418 | 0.9018 | |
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| 0.0001 | 6.0 | 750 | 0.5245 | 0.9077 | |
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| 0.0863 | 7.0 | 875 | 0.6622 | 0.8571 | |
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| 0.059 | 8.0 | 1000 | 0.6755 | 0.8869 | |
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| 0.0153 | 9.0 | 1125 | 0.6671 | 0.9048 | |
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| 0.0014 | 10.0 | 1250 | 0.6834 | 0.8988 | |
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| 0.0 | 11.0 | 1375 | 0.6805 | 0.9018 | |
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| 0.0 | 12.0 | 1500 | 0.6765 | 0.9048 | |
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| 0.0 | 13.0 | 1625 | 0.6773 | 0.9018 | |
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| 0.0 | 14.0 | 1750 | 0.6771 | 0.9018 | |
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| 0.0 | 15.0 | 1875 | 0.6772 | 0.9018 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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