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Model save
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README.md
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---
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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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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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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.
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- Accuracy: 0.
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## Model description
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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:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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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:
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### Training results
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| Training Loss | Epoch
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### Framework versions
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- Transformers 4.44.
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- Pytorch 2.4.
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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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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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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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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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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