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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: 0.8845794392523364 |
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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: 0.3329 |
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- Accuracy: 0.8846 |
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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: 240 |
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- eval_batch_size: 240 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 960 |
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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: 15 |
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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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| 2.7644 | 0.99 | 20 | 1.5288 | 0.6140 | |
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| 0.8358 | 1.98 | 40 | 0.6582 | 0.7584 | |
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| 0.5367 | 2.96 | 60 | 0.4823 | 0.8229 | |
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| 0.4645 | 4.0 | 81 | 0.4269 | 0.8556 | |
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| 0.4218 | 4.99 | 101 | 0.3912 | 0.8659 | |
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| 0.391 | 5.98 | 121 | 0.3637 | 0.8748 | |
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| 0.3789 | 6.96 | 141 | 0.3554 | 0.8748 | |
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| 0.3684 | 8.0 | 162 | 0.3489 | 0.8790 | |
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| 0.3671 | 8.99 | 182 | 0.3503 | 0.8813 | |
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| 0.3545 | 9.98 | 202 | 0.3442 | 0.8818 | |
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| 0.339 | 10.96 | 222 | 0.3369 | 0.8841 | |
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| 0.3225 | 12.0 | 243 | 0.3424 | 0.8808 | |
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| 0.3228 | 12.99 | 263 | 0.3386 | 0.8850 | |
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| 0.3141 | 13.98 | 283 | 0.3344 | 0.8846 | |
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| 0.3219 | 14.81 | 300 | 0.3329 | 0.8846 | |
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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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