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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-22k-224 |
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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: convnextv2-base-22k-224-finetuned-eurosat-2 |
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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: train |
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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: 0.9096045197740112 |
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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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# convnextv2-base-22k-224-finetuned-eurosat-2 |
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This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3801 |
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- Accuracy: 0.9096 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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| 0.5227 | 1.0 | 99 | 0.5333 | 0.7797 | |
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| 0.4248 | 1.99 | 198 | 0.4145 | 0.8531 | |
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| 0.2998 | 2.99 | 297 | 0.3307 | 0.8757 | |
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| 0.1704 | 4.0 | 397 | 0.2664 | 0.8927 | |
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| 0.0684 | 5.0 | 496 | 0.4353 | 0.8701 | |
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| 0.1546 | 5.99 | 595 | 0.3920 | 0.8870 | |
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| 0.0593 | 6.99 | 694 | 0.3801 | 0.9096 | |
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| 0.0745 | 8.0 | 794 | 0.4030 | 0.8983 | |
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| 0.0877 | 9.0 | 893 | 0.3846 | 0.9040 | |
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| 0.09 | 9.97 | 990 | 0.3816 | 0.9040 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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