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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-huge-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-huge-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: 0.8897196261682243 |
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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-huge-1k-224-finetuned-cassava-leaf-disease |
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This model is a fine-tuned version of [facebook/convnextv2-huge-1k-224](https://huggingface.co/facebook/convnextv2-huge-1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3433 |
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- Accuracy: 0.8897 |
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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: 120 |
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- eval_batch_size: 120 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 480 |
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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: 10 |
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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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| 7.9894 | 0.25 | 10 | 4.9516 | 0.0206 | |
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| 2.7782 | 0.5 | 20 | 1.6759 | 0.6196 | |
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| 1.2699 | 0.75 | 30 | 0.9878 | 0.6626 | |
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| 0.8247 | 0.99 | 40 | 0.6755 | 0.7640 | |
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| 0.6353 | 1.24 | 50 | 0.5472 | 0.8079 | |
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| 0.5418 | 1.49 | 60 | 0.4924 | 0.8369 | |
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| 0.4577 | 1.74 | 70 | 0.4422 | 0.8537 | |
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| 0.4627 | 1.99 | 80 | 0.3943 | 0.8706 | |
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| 0.4235 | 2.24 | 90 | 0.3868 | 0.8715 | |
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| 0.4068 | 2.48 | 100 | 0.3879 | 0.8645 | |
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| 0.4088 | 2.73 | 110 | 0.4149 | 0.8579 | |
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| 0.3866 | 2.98 | 120 | 0.3489 | 0.8836 | |
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| 0.3776 | 3.23 | 130 | 0.3731 | 0.8743 | |
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| 0.3303 | 3.48 | 140 | 0.3719 | 0.8734 | |
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| 0.3548 | 3.73 | 150 | 0.3917 | 0.8668 | |
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| 0.3638 | 3.98 | 160 | 0.3561 | 0.8738 | |
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| 0.3292 | 4.22 | 170 | 0.3518 | 0.8855 | |
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| 0.3363 | 4.47 | 180 | 0.3561 | 0.8850 | |
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| 0.3123 | 4.72 | 190 | 0.3452 | 0.8794 | |
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| 0.3395 | 4.97 | 200 | 0.3385 | 0.8841 | |
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| 0.2851 | 5.22 | 210 | 0.3467 | 0.8883 | |
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| 0.3113 | 5.47 | 220 | 0.3393 | 0.8841 | |
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| 0.3035 | 5.71 | 230 | 0.3444 | 0.8785 | |
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| 0.3123 | 5.96 | 240 | 0.3321 | 0.8804 | |
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| 0.2683 | 6.21 | 250 | 0.3407 | 0.8813 | |
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| 0.2811 | 6.46 | 260 | 0.3396 | 0.8850 | |
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| 0.2779 | 6.71 | 270 | 0.3318 | 0.8869 | |
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| 0.2733 | 6.96 | 280 | 0.3342 | 0.8897 | |
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| 0.2661 | 7.2 | 290 | 0.3303 | 0.8916 | |
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| 0.2588 | 7.45 | 300 | 0.3387 | 0.8921 | |
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| 0.2586 | 7.7 | 310 | 0.3373 | 0.8888 | |
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| 0.2641 | 7.95 | 320 | 0.3328 | 0.8860 | |
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| 0.2408 | 8.2 | 330 | 0.3490 | 0.8818 | |
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| 0.2375 | 8.45 | 340 | 0.3419 | 0.8846 | |
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| 0.2507 | 8.7 | 350 | 0.3473 | 0.8874 | |
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| 0.2555 | 8.94 | 360 | 0.3382 | 0.8874 | |
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| 0.2299 | 9.19 | 370 | 0.3399 | 0.8888 | |
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| 0.2309 | 9.44 | 380 | 0.3415 | 0.8855 | |
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| 0.2344 | 9.69 | 390 | 0.3431 | 0.8897 | |
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| 0.2253 | 9.94 | 400 | 0.3433 | 0.8897 | |
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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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