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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: convnextv2-base-22k-224-finetuned-eurosat-50 |
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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: Augmented-Final |
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split: train |
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args: Augmented-Final |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9146968139773896 |
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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-50 |
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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: 0.2875 |
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- Accuracy: 0.9147 |
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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-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 0.9 |
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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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| 1.9019 | 1.0 | 122 | 1.9510 | 0.1727 | |
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| 1.7782 | 2.0 | 244 | 1.8239 | 0.3073 | |
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| 1.6214 | 3.0 | 366 | 1.6121 | 0.4913 | |
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| 1.3495 | 4.0 | 488 | 1.3064 | 0.6238 | |
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| 1.0994 | 5.0 | 610 | 1.0243 | 0.7163 | |
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| 0.8866 | 6.0 | 732 | 0.8165 | 0.7564 | |
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| 0.7282 | 7.0 | 854 | 0.6637 | 0.7996 | |
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| 0.6211 | 8.0 | 976 | 0.5623 | 0.8160 | |
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| 0.5114 | 9.0 | 1098 | 0.4681 | 0.8551 | |
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| 0.3835 | 10.0 | 1220 | 0.3917 | 0.8787 | |
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| 0.3543 | 11.0 | 1342 | 0.3122 | 0.9013 | |
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| 0.3534 | 12.0 | 1464 | 0.2875 | 0.9147 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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