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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-base-fa-disabled-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: 0.9164021164021164 |
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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-fa-disabled-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: 0.3027 |
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- Accuracy: 0.9164 |
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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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| 0.8554 | 0.9910 | 83 | 0.5252 | 0.8323 | |
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| 0.8162 | 1.9940 | 167 | 0.4597 | 0.8598 | |
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| 0.7303 | 2.9970 | 251 | 0.4403 | 0.8587 | |
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| 0.5644 | 4.0 | 335 | 0.3922 | 0.8746 | |
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| 0.5672 | 4.9910 | 418 | 0.3784 | 0.8857 | |
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| 0.454 | 5.9940 | 502 | 0.3856 | 0.8831 | |
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| 0.4379 | 6.9970 | 586 | 0.3510 | 0.8889 | |
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| 0.3356 | 8.0 | 670 | 0.3187 | 0.9063 | |
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| 0.2877 | 8.9910 | 753 | 0.3209 | 0.9116 | |
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| 0.2717 | 9.9104 | 830 | 0.3027 | 0.9164 | |
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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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