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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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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: dinov2-finetuned-har |
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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: test |
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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: 0.9148148148148149 |
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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-finetuned-har |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3078 |
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- Accuracy: 0.9148 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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| 0.9429 | 0.9910 | 83 | 0.5624 | 0.8328 | |
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| 0.7912 | 1.9940 | 167 | 0.4755 | 0.8587 | |
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| 0.7371 | 2.9970 | 251 | 0.4584 | 0.8550 | |
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| 0.5915 | 4.0 | 335 | 0.3870 | 0.8762 | |
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| 0.5635 | 4.9910 | 418 | 0.4037 | 0.8704 | |
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| 0.498 | 5.9940 | 502 | 0.3876 | 0.8804 | |
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| 0.4541 | 6.9970 | 586 | 0.3612 | 0.8884 | |
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| 0.3513 | 8.0 | 670 | 0.3240 | 0.9053 | |
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| 0.2963 | 8.9910 | 753 | 0.3176 | 0.9116 | |
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| 0.2815 | 9.9104 | 830 | 0.3078 | 0.9148 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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