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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-152 |
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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: resnet-152-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: 0.7397196261682243 |
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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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# resnet-152-finetuned-cassava-leaf-disease |
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This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7961 |
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- Accuracy: 0.7397 |
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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: 480 |
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- eval_batch_size: 480 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 1920 |
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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: 30 |
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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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| 7.309 | 0.98 | 10 | 7.0088 | 0.0028 | |
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| 6.9946 | 1.95 | 20 | 6.4363 | 0.0061 | |
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| 6.4082 | 2.93 | 30 | 5.5840 | 0.0673 | |
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| 5.6018 | 4.0 | 41 | 4.1884 | 0.3687 | |
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| 4.5652 | 4.98 | 51 | 3.3123 | 0.4640 | |
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| 3.6106 | 5.95 | 61 | 2.7918 | 0.5136 | |
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| 2.9184 | 6.93 | 71 | 2.3762 | 0.5636 | |
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| 2.3775 | 8.0 | 82 | 1.9163 | 0.6084 | |
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| 2.0119 | 8.98 | 92 | 1.7038 | 0.6299 | |
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| 1.7519 | 9.95 | 102 | 1.5220 | 0.6411 | |
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| 1.4995 | 10.93 | 112 | 1.3828 | 0.6575 | |
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| 1.3648 | 12.0 | 123 | 1.2715 | 0.6668 | |
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| 1.2357 | 12.98 | 133 | 1.2040 | 0.6692 | |
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| 1.1606 | 13.95 | 143 | 1.1249 | 0.6785 | |
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| 1.0793 | 14.93 | 153 | 1.0600 | 0.6897 | |
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| 1.0332 | 16.0 | 164 | 1.0160 | 0.6935 | |
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| 0.9724 | 16.98 | 174 | 0.9706 | 0.7047 | |
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| 0.9349 | 17.95 | 184 | 0.9524 | 0.7075 | |
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| 0.895 | 18.93 | 194 | 0.9210 | 0.7093 | |
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| 0.8913 | 20.0 | 205 | 0.9007 | 0.7168 | |
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| 0.8519 | 20.98 | 215 | 0.8672 | 0.7229 | |
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| 0.8434 | 21.95 | 225 | 0.8432 | 0.7252 | |
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| 0.8346 | 22.93 | 235 | 0.8307 | 0.7304 | |
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| 0.8019 | 24.0 | 246 | 0.8154 | 0.7308 | |
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| 0.8001 | 24.98 | 256 | 0.8121 | 0.7327 | |
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| 0.7813 | 25.95 | 266 | 0.8036 | 0.7341 | |
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| 0.7845 | 26.93 | 276 | 0.8025 | 0.7383 | |
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| 0.7635 | 28.0 | 287 | 0.7934 | 0.7444 | |
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| 0.7782 | 28.98 | 297 | 0.7910 | 0.7421 | |
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| 0.7634 | 29.27 | 300 | 0.7961 | 0.7397 | |
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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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