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---
base_model: syedmuhammad/ConvNextV2-Diabetec-Retinopathy
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: ConvNext-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: 0.9900990099009901
---
<!-- 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. -->
# ConvNext-V2-Retinopathy
This model is a fine-tuned version of [syedmuhammad/ConvNextV2-Diabetec-Retinopathy](https://huggingface.co/syedmuhammad/ConvNextV2-Diabetec-Retinopathy) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0219
- Accuracy: 0.9901
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.125 | 1.0 | 113 | 0.0339 | 0.9901 |
| 0.2206 | 2.0 | 227 | 0.0139 | 0.9901 |
| 0.1751 | 3.0 | 340 | 0.0114 | 0.9950 |
| 0.0599 | 4.0 | 454 | 0.0277 | 0.9950 |
| 0.1122 | 5.0 | 567 | 0.0328 | 0.9950 |
| 0.093 | 6.0 | 681 | 0.0240 | 0.9901 |
| 0.0673 | 7.0 | 794 | 0.0251 | 0.9950 |
| 0.0718 | 8.0 | 908 | 0.0458 | 0.9851 |
| 0.0632 | 9.0 | 1021 | 0.0477 | 0.9901 |
| 0.0263 | 10.0 | 1135 | 0.0399 | 0.9950 |
| 0.0304 | 11.0 | 1248 | 0.0295 | 0.9901 |
| 0.0892 | 12.0 | 1362 | 0.0330 | 0.9950 |
| 0.0227 | 13.0 | 1475 | 0.0287 | 0.9901 |
| 0.0253 | 14.0 | 1589 | 0.0262 | 0.9901 |
| 0.1242 | 14.93 | 1695 | 0.0219 | 0.9901 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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