---
library_name: transformers
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: mobilenet_v2_1.0_224-finetuned-plantdisease
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9777191259513872
---

<!-- 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. -->

# mobilenet_v2_1.0_224-finetuned-plantdisease

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0702
- Accuracy: 0.9777

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.3974        | 0.9996 | 1145  | 0.3599          | 0.8979   |
| 0.2155        | 2.0    | 2291  | 0.1525          | 0.9603   |
| 0.2058        | 2.9996 | 3436  | 0.1492          | 0.9559   |
| 0.1524        | 4.0    | 4582  | 0.1025          | 0.9694   |
| 0.1274        | 4.9996 | 5727  | 0.0928          | 0.9706   |
| 0.1141        | 6.0    | 6873  | 0.0874          | 0.9723   |
| 0.1275        | 6.9996 | 8018  | 0.1226          | 0.9620   |
| 0.1323        | 8.0    | 9164  | 0.0702          | 0.9777   |
| 0.1212        | 8.9996 | 10309 | 0.1257          | 0.9607   |
| 0.0981        | 9.9956 | 11450 | 0.0750          | 0.9751   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1