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README.md
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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-small-imagenet1k-1-layer
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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-small-imagenet1k-1-layer-finetuned-eurosat
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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-small-imagenet1k-1-layer-finetuned-eurosat
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This model is a fine-tuned version of [facebook/dinov2-small-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-small-imagenet1k-1-layer) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2994
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- Accuracy: 0.9212
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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: Use 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: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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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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| 1.9886 | 1.0 | 26 | 0.8828 | 0.7717 |
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| 0.645 | 2.0 | 52 | 0.4112 | 0.8859 |
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| 0.4834 | 3.0 | 78 | 0.2994 | 0.9212 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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runs/Dec16_05-01-50_c54122f7729c/events.out.tfevents.1734325311.c54122f7729c.281.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:698c9c1cc910e3de45702644fcbdeab503134350aec22b8e61449297d1388057
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size 10069
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