---
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_tl
  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_tl

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: 1.3083
- Accuracy: 0.5952

## 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: 128
- eval_batch_size: 128
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0633        | 1.0   | 63   | 2.0143          | 0.3452   |
| 1.9625        | 2.0   | 126  | 1.8719          | 0.5060   |
| 1.8119        | 3.0   | 189  | 1.7332          | 0.5      |
| 1.6826        | 4.0   | 252  | 1.6271          | 0.5268   |
| 1.5879        | 5.0   | 315  | 1.5436          | 0.5595   |
| 1.516         | 6.0   | 378  | 1.4871          | 0.5536   |
| 1.4572        | 7.0   | 441  | 1.4566          | 0.5655   |
| 1.4104        | 8.0   | 504  | 1.4224          | 0.5685   |
| 1.3734        | 9.0   | 567  | 1.4033          | 0.5685   |
| 1.3414        | 10.0  | 630  | 1.3735          | 0.5952   |
| 1.3186        | 11.0  | 693  | 1.3579          | 0.5714   |
| 1.2972        | 12.0  | 756  | 1.3402          | 0.5923   |
| 1.2862        | 13.0  | 819  | 1.3342          | 0.5893   |
| 1.2716        | 14.0  | 882  | 1.3271          | 0.5863   |
| 1.2632        | 15.0  | 945  | 1.3210          | 0.6042   |
| 1.2546        | 16.0  | 1008 | 1.3146          | 0.5923   |
| 1.2485        | 17.0  | 1071 | 1.3061          | 0.6012   |
| 1.25          | 18.0  | 1134 | 1.3090          | 0.5923   |
| 1.2457        | 19.0  | 1197 | 1.3106          | 0.6042   |
| 1.2466        | 20.0  | 1260 | 1.3083          | 0.5952   |


### Framework versions

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