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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-1k-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-1k-224-finetuned-cassava-leaf-disease |
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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: 0.8841121495327103 |
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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-1k-224-finetuned-cassava-leaf-disease |
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This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3624 |
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- Accuracy: 0.8841 |
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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: 360 |
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- eval_batch_size: 360 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1440 |
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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: 20 |
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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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| 7.5825 | 0.96 | 13 | 2.5252 | 0.4874 | |
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| 2.4869 | 2.0 | 27 | 1.0172 | 0.6388 | |
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| 0.7793 | 2.96 | 40 | 0.6048 | 0.7925 | |
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| 0.5807 | 4.0 | 54 | 0.4873 | 0.8327 | |
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| 0.5079 | 4.96 | 67 | 0.4330 | 0.8514 | |
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| 0.4363 | 6.0 | 81 | 0.4140 | 0.8668 | |
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| 0.4118 | 6.96 | 94 | 0.3962 | 0.8743 | |
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| 0.3918 | 8.0 | 108 | 0.3924 | 0.8748 | |
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| 0.3669 | 8.96 | 121 | 0.3816 | 0.8822 | |
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| 0.3687 | 10.0 | 135 | 0.3784 | 0.8776 | |
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| 0.3645 | 10.96 | 148 | 0.3684 | 0.8846 | |
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| 0.349 | 12.0 | 162 | 0.3706 | 0.8804 | |
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| 0.3341 | 12.96 | 175 | 0.3678 | 0.8813 | |
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| 0.3304 | 14.0 | 189 | 0.3618 | 0.8794 | |
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| 0.3318 | 14.96 | 202 | 0.3677 | 0.8808 | |
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| 0.3178 | 16.0 | 216 | 0.3626 | 0.8818 | |
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| 0.3209 | 16.96 | 229 | 0.3606 | 0.8822 | |
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| 0.3129 | 18.0 | 243 | 0.3615 | 0.8836 | |
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| 0.3013 | 18.96 | 256 | 0.3627 | 0.8841 | |
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| 0.3046 | 19.26 | 260 | 0.3624 | 0.8841 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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