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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: 0.9148148148148149
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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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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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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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