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--- |
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license: apache-2.0 |
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base_model: facebook/convnext-tiny-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: convnext-tiny-224-finetuned-eurosat-albumentations |
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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: 0.6366906474820144 |
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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-albumentations |
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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: 0.8091 |
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- Accuracy: 0.6367 |
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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: 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: 12 |
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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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| 1.1311 | 0.96 | 19 | 1.0751 | 0.3813 | |
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| 1.0477 | 1.97 | 39 | 1.0354 | 0.5036 | |
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| 0.9932 | 2.99 | 59 | 1.0054 | 0.5144 | |
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| 0.9445 | 4.0 | 79 | 0.9702 | 0.5432 | |
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| 0.8911 | 4.96 | 98 | 0.9461 | 0.5647 | |
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| 0.8339 | 5.97 | 118 | 0.9079 | 0.5827 | |
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| 0.7923 | 6.99 | 138 | 0.8767 | 0.5899 | |
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| 0.751 | 8.0 | 158 | 0.8521 | 0.6187 | |
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| 0.7222 | 8.96 | 177 | 0.8315 | 0.6223 | |
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| 0.688 | 9.97 | 197 | 0.8183 | 0.6259 | |
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| 0.6734 | 10.99 | 217 | 0.8091 | 0.6367 | |
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| 0.6734 | 11.54 | 228 | 0.8090 | 0.6331 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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