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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/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: 0.958904109589041 |
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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: 0.2746 |
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- Accuracy: 0.9589 |
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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: 50 |
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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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| 0.0418 | 0.9362 | 11 | 0.2497 | 0.9041 | |
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| 0.0349 | 1.9574 | 23 | 0.2377 | 0.9041 | |
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| 0.0231 | 2.9787 | 35 | 0.2695 | 0.8904 | |
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| 0.0154 | 4.0 | 47 | 0.2185 | 0.9041 | |
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| 0.0061 | 4.9362 | 58 | 0.2810 | 0.9178 | |
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| 0.0023 | 5.9574 | 70 | 0.2905 | 0.9315 | |
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| 0.0029 | 6.9787 | 82 | 0.2052 | 0.9315 | |
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| 0.0013 | 8.0 | 94 | 0.2333 | 0.9178 | |
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| 0.0009 | 8.9362 | 105 | 0.2262 | 0.9315 | |
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| 0.008 | 9.9574 | 117 | 0.2247 | 0.9178 | |
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| 0.0014 | 10.9787 | 129 | 0.3200 | 0.9041 | |
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| 0.0005 | 12.0 | 141 | 0.2643 | 0.9178 | |
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| 0.0006 | 12.9362 | 152 | 0.2911 | 0.9178 | |
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| 0.0007 | 13.9574 | 164 | 0.2567 | 0.9178 | |
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| 0.0009 | 14.9787 | 176 | 0.3170 | 0.9178 | |
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| 0.0052 | 16.0 | 188 | 0.2435 | 0.9315 | |
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| 0.0005 | 16.9362 | 199 | 0.2746 | 0.9589 | |
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| 0.0004 | 17.9574 | 211 | 0.2347 | 0.9315 | |
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| 0.002 | 18.9787 | 223 | 0.2999 | 0.9178 | |
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| 0.0021 | 20.0 | 235 | 0.2648 | 0.9178 | |
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| 0.0003 | 20.9362 | 246 | 0.2609 | 0.9178 | |
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| 0.0002 | 21.9574 | 258 | 0.2709 | 0.9315 | |
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| 0.0004 | 22.9787 | 270 | 0.2359 | 0.9315 | |
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| 0.005 | 24.0 | 282 | 0.2484 | 0.9178 | |
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| 0.0011 | 24.9362 | 293 | 0.3019 | 0.9178 | |
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| 0.0012 | 25.9574 | 305 | 0.2715 | 0.9178 | |
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| 0.0003 | 26.9787 | 317 | 0.2486 | 0.9315 | |
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| 0.0009 | 28.0 | 329 | 0.2472 | 0.9315 | |
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| 0.0002 | 28.9362 | 340 | 0.2449 | 0.9315 | |
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| 0.0002 | 29.9574 | 352 | 0.2480 | 0.9315 | |
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| 0.0002 | 30.9787 | 364 | 0.2520 | 0.9315 | |
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| 0.0002 | 32.0 | 376 | 0.2528 | 0.9315 | |
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| 0.0001 | 32.9362 | 387 | 0.2520 | 0.9315 | |
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| 0.0002 | 33.9574 | 399 | 0.2503 | 0.9315 | |
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| 0.0001 | 34.9787 | 411 | 0.2508 | 0.9315 | |
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| 0.0001 | 36.0 | 423 | 0.2493 | 0.9315 | |
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| 0.0008 | 36.9362 | 434 | 0.2558 | 0.9315 | |
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| 0.0001 | 37.9574 | 446 | 0.2616 | 0.9315 | |
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| 0.0001 | 38.9787 | 458 | 0.2623 | 0.9315 | |
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| 0.0011 | 40.0 | 470 | 0.2617 | 0.9315 | |
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| 0.0002 | 40.9362 | 481 | 0.2532 | 0.9315 | |
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| 0.0001 | 41.9574 | 493 | 0.2495 | 0.9315 | |
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| 0.0001 | 42.9787 | 505 | 0.2478 | 0.9315 | |
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| 0.0001 | 44.0 | 517 | 0.2479 | 0.9315 | |
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| 0.0001 | 44.9362 | 528 | 0.2481 | 0.9315 | |
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| 0.0001 | 45.9574 | 540 | 0.2481 | 0.9315 | |
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| 0.002 | 46.8085 | 550 | 0.2475 | 0.9315 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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