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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: resnet-50_rice-leaf-disease-augmented-v2_fft |
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results: [] |
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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-50_rice-leaf-disease-augmented-v2_fft |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1313 |
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- Accuracy: 0.6726 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 2.0639 | 1.0 | 125 | 2.0235 | 0.3393 | |
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| 1.9838 | 2.0 | 250 | 1.9041 | 0.4911 | |
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| 1.8621 | 3.0 | 375 | 1.7795 | 0.5238 | |
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| 1.7579 | 4.0 | 500 | 1.6965 | 0.5446 | |
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| 1.6945 | 5.0 | 625 | 1.6616 | 0.5625 | |
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| 1.6741 | 6.0 | 750 | 1.6497 | 0.5565 | |
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| 1.6042 | 7.0 | 875 | 1.5223 | 0.5685 | |
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| 1.4807 | 8.0 | 1000 | 1.4272 | 0.5893 | |
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| 1.3988 | 9.0 | 1125 | 1.3771 | 0.6101 | |
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| 1.3575 | 10.0 | 1250 | 1.3642 | 0.6071 | |
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| 1.3377 | 11.0 | 1375 | 1.3011 | 0.6220 | |
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| 1.2331 | 12.0 | 1500 | 1.2030 | 0.6548 | |
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| 1.1439 | 13.0 | 1625 | 1.1507 | 0.6577 | |
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| 1.0902 | 14.0 | 1750 | 1.1259 | 0.6548 | |
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| 1.0735 | 15.0 | 1875 | 1.1313 | 0.6726 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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