---
license: other
base_model: google/mobilenet_v2_1.4_224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: MobileNet-V2-Retinopathy
  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: 0.9306930693069307
---

<!-- 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-Retinopathy

This model is a fine-tuned version of [google/mobilenet_v2_1.4_224](https://huggingface.co/google/mobilenet_v2_1.4_224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2044
- Accuracy: 0.9307

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4403        | 1.0   | 113  | 0.5330          | 0.7079   |
| 0.5538        | 2.0   | 227  | 0.4312          | 0.7723   |
| 0.542         | 3.0   | 340  | 0.5137          | 0.7426   |
| 0.4776        | 4.0   | 454  | 0.4656          | 0.7723   |
| 0.4244        | 5.0   | 567  | 1.0400          | 0.5990   |
| 0.4694        | 6.0   | 681  | 0.5936          | 0.7228   |
| 0.4494        | 7.0   | 794  | 0.4667          | 0.7822   |
| 0.4647        | 8.0   | 908  | 0.2629          | 0.8960   |
| 0.3646        | 9.0   | 1021 | 0.2287          | 0.8861   |
| 0.4827        | 10.0  | 1135 | 1.7967          | 0.5149   |
| 0.3679        | 11.0  | 1248 | 0.4184          | 0.8267   |
| 0.3454        | 12.0  | 1362 | 0.1885          | 0.9406   |
| 0.3562        | 13.0  | 1475 | 0.2798          | 0.9059   |
| 0.3397        | 14.0  | 1589 | 1.6444          | 0.5891   |
| 0.4047        | 14.93 | 1695 | 0.2044          | 0.9307   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1