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---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224_rice-disease-02_112024
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-base-patch4-window7-224_rice-disease-02_112024
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co./microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2147
- Accuracy: 0.9281
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.7761 | 1.0 | 212 | 0.7405 | 0.9638 |
| 0.6771 | 2.0 | 424 | 0.8476 | 0.4818 |
| 0.4223 | 3.0 | 636 | 0.8756 | 0.3695 |
| 0.3403 | 4.0 | 848 | 0.8922 | 0.3168 |
| 0.2958 | 5.0 | 1060 | 0.9082 | 0.2835 |
| 0.2709 | 6.0 | 1272 | 0.2664 | 0.9075 |
| 0.2494 | 7.0 | 1484 | 0.2498 | 0.9168 |
| 0.2395 | 8.0 | 1696 | 0.2420 | 0.9182 |
| 0.2286 | 9.0 | 1908 | 0.2365 | 0.9215 |
| 0.22 | 10.0 | 2120 | 0.2296 | 0.9202 |
| 0.2137 | 11.0 | 2332 | 0.2230 | 0.9242 |
| 0.2093 | 12.0 | 2544 | 0.2178 | 0.9281 |
| 0.202 | 13.0 | 2756 | 0.2162 | 0.9295 |
| 0.2017 | 14.0 | 2968 | 0.2151 | 0.9275 |
| 0.1986 | 15.0 | 3180 | 0.2147 | 0.9281 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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