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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-large-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-large-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: 0.8691588785046729 |
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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-large-1k-224-finetuned-cassava-leaf-disease |
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This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4210 |
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- Accuracy: 0.8692 |
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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: 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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| 8.2962 | 0.49 | 10 | 5.4110 | 0.0033 | |
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| 3.1666 | 0.99 | 20 | 2.0615 | 0.5883 | |
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| 1.4693 | 1.48 | 30 | 1.0935 | 0.6084 | |
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| 0.8718 | 1.98 | 40 | 0.7291 | 0.7463 | |
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| 0.6252 | 2.47 | 50 | 0.5894 | 0.7916 | |
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| 0.5198 | 2.96 | 60 | 0.5204 | 0.8299 | |
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| 0.4517 | 3.46 | 70 | 0.4658 | 0.8393 | |
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| 0.4266 | 3.95 | 80 | 0.4664 | 0.8407 | |
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| 0.4049 | 4.44 | 90 | 0.4337 | 0.8579 | |
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| 0.3817 | 4.94 | 100 | 0.4247 | 0.8523 | |
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| 0.3696 | 5.43 | 110 | 0.4146 | 0.8621 | |
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| 0.3577 | 5.93 | 120 | 0.4058 | 0.8607 | |
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| 0.3577 | 6.42 | 130 | 0.4047 | 0.8636 | |
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| 0.3354 | 6.91 | 140 | 0.3985 | 0.8617 | |
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| 0.3356 | 7.41 | 150 | 0.4025 | 0.8645 | |
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| 0.3286 | 7.9 | 160 | 0.4054 | 0.8673 | |
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| 0.3225 | 8.4 | 170 | 0.4062 | 0.8631 | |
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| 0.317 | 8.89 | 180 | 0.4007 | 0.8692 | |
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| 0.3101 | 9.38 | 190 | 0.3931 | 0.8701 | |
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| 0.293 | 9.88 | 200 | 0.3928 | 0.8682 | |
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| 0.2992 | 10.37 | 210 | 0.3942 | 0.8668 | |
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| 0.2968 | 10.86 | 220 | 0.3892 | 0.8692 | |
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| 0.2794 | 11.36 | 230 | 0.3988 | 0.8701 | |
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| 0.2707 | 11.85 | 240 | 0.3865 | 0.8762 | |
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| 0.2883 | 12.35 | 250 | 0.4040 | 0.8640 | |
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| 0.2784 | 12.84 | 260 | 0.3930 | 0.8692 | |
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| 0.2667 | 13.33 | 270 | 0.3985 | 0.8701 | |
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| 0.2642 | 13.83 | 280 | 0.4160 | 0.8668 | |
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| 0.2612 | 14.32 | 290 | 0.4086 | 0.8687 | |
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| 0.2586 | 14.81 | 300 | 0.3990 | 0.8668 | |
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| 0.2483 | 15.31 | 310 | 0.4111 | 0.8720 | |
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| 0.254 | 15.8 | 320 | 0.4082 | 0.8748 | |
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| 0.2283 | 16.3 | 330 | 0.4165 | 0.8668 | |
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| 0.246 | 16.79 | 340 | 0.4264 | 0.8692 | |
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| 0.2365 | 17.28 | 350 | 0.4185 | 0.8692 | |
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| 0.2388 | 17.78 | 360 | 0.4152 | 0.8650 | |
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| 0.2401 | 18.27 | 370 | 0.4169 | 0.8659 | |
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| 0.2334 | 18.77 | 380 | 0.4187 | 0.8696 | |
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| 0.2245 | 19.26 | 390 | 0.4192 | 0.8692 | |
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| 0.2291 | 19.75 | 400 | 0.4210 | 0.8692 | |
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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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