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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-22k-384 |
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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-384-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: 0.8785046728971962 |
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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-384-finetuned-cassava-leaf-disease |
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This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3755 |
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- Accuracy: 0.8785 |
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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: 140 |
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- eval_batch_size: 140 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 560 |
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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: 16 |
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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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| 0.7713 | 0.99 | 34 | 0.5754 | 0.7949 | |
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| 0.3953 | 2.0 | 69 | 0.3769 | 0.8650 | |
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| 0.3478 | 2.99 | 103 | 0.3717 | 0.8673 | |
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| 0.3296 | 4.0 | 138 | 0.3696 | 0.8752 | |
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| 0.3058 | 4.99 | 172 | 0.3387 | 0.8808 | |
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| 0.2791 | 6.0 | 207 | 0.3480 | 0.8804 | |
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| 0.2541 | 6.99 | 241 | 0.3483 | 0.8799 | |
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| 0.247 | 8.0 | 276 | 0.3590 | 0.8743 | |
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| 0.2395 | 8.99 | 310 | 0.3505 | 0.8794 | |
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| 0.2139 | 10.0 | 345 | 0.3702 | 0.8766 | |
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| 0.2116 | 10.99 | 379 | 0.3702 | 0.8766 | |
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| 0.204 | 12.0 | 414 | 0.3661 | 0.8762 | |
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| 0.183 | 12.99 | 448 | 0.3705 | 0.8776 | |
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| 0.1856 | 14.0 | 483 | 0.3861 | 0.8780 | |
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| 0.1641 | 14.99 | 517 | 0.3758 | 0.8766 | |
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| 0.1784 | 15.77 | 544 | 0.3755 | 0.8785 | |
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### Framework versions |
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- Transformers 4.39.3 |
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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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