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--- |
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license: apache-2.0 |
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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: convnext-tiny-224-finetuned-eurosat-att-auto |
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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: 0.9506172839506173 |
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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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# convnext-tiny-224-finetuned-eurosat-att-auto |
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This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5076 |
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- Accuracy: 0.9506 |
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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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| 1.5583 | 0.97 | 23 | 1.6008 | 0.7160 | |
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| 1.2953 | 1.97 | 46 | 1.2957 | 0.7531 | |
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| 0.9488 | 2.97 | 69 | 1.0720 | 0.8148 | |
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| 0.7036 | 3.97 | 92 | 0.8965 | 0.8642 | |
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| 0.5446 | 4.97 | 115 | 0.7574 | 0.9383 | |
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| 0.4113 | 5.97 | 138 | 0.6522 | 0.9383 | |
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| 0.2259 | 6.97 | 161 | 0.5720 | 0.9383 | |
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| 0.1863 | 7.97 | 184 | 0.5076 | 0.9506 | |
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| 0.1443 | 8.97 | 207 | 0.4795 | 0.9383 | |
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| 0.1289 | 9.97 | 230 | 0.4685 | 0.9383 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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