---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: resnet-50_rice-leaf-disease-augmented-v2_fft
  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. -->

# resnet-50_rice-leaf-disease-augmented-v2_fft

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1313
- Accuracy: 0.6726

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0639        | 1.0   | 125  | 2.0235          | 0.3393   |
| 1.9838        | 2.0   | 250  | 1.9041          | 0.4911   |
| 1.8621        | 3.0   | 375  | 1.7795          | 0.5238   |
| 1.7579        | 4.0   | 500  | 1.6965          | 0.5446   |
| 1.6945        | 5.0   | 625  | 1.6616          | 0.5625   |
| 1.6741        | 6.0   | 750  | 1.6497          | 0.5565   |
| 1.6042        | 7.0   | 875  | 1.5223          | 0.5685   |
| 1.4807        | 8.0   | 1000 | 1.4272          | 0.5893   |
| 1.3988        | 9.0   | 1125 | 1.3771          | 0.6101   |
| 1.3575        | 10.0  | 1250 | 1.3642          | 0.6071   |
| 1.3377        | 11.0  | 1375 | 1.3011          | 0.6220   |
| 1.2331        | 12.0  | 1500 | 1.2030          | 0.6548   |
| 1.1439        | 13.0  | 1625 | 1.1507          | 0.6577   |
| 1.0902        | 14.0  | 1750 | 1.1259          | 0.6548   |
| 1.0735        | 15.0  | 1875 | 1.1313          | 0.6726   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0