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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-randomflip |
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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: 0.8766355140186916 |
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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-randomflip |
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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: 0.3704 |
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- Accuracy: 0.8766 |
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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: 400 |
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- eval_batch_size: 400 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1600 |
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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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| 1.5605 | 0.98 | 12 | 1.2754 | 0.6150 | |
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| 1.2015 | 1.96 | 24 | 0.9009 | 0.6290 | |
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| 0.9048 | 2.94 | 36 | 0.6987 | 0.7701 | |
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| 0.7362 | 4.0 | 49 | 0.5497 | 0.8206 | |
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| 0.5294 | 4.98 | 61 | 0.4712 | 0.8542 | |
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| 0.4777 | 5.96 | 73 | 0.4451 | 0.8547 | |
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| 0.458 | 6.94 | 85 | 0.4197 | 0.8579 | |
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| 0.4208 | 8.0 | 98 | 0.4084 | 0.8682 | |
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| 0.4042 | 8.98 | 110 | 0.3930 | 0.8692 | |
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| 0.4071 | 9.96 | 122 | 0.3879 | 0.8743 | |
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| 0.3868 | 10.94 | 134 | 0.3923 | 0.8715 | |
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| 0.3849 | 12.0 | 147 | 0.3763 | 0.8748 | |
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| 0.3744 | 12.98 | 159 | 0.3732 | 0.8776 | |
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| 0.3739 | 13.96 | 171 | 0.3708 | 0.8748 | |
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| 0.361 | 14.94 | 183 | 0.3693 | 0.8818 | |
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| 0.3725 | 15.67 | 192 | 0.3704 | 0.8766 | |
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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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