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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- martinezomg/diabetic-retinopathy
metrics:
- accuracy
pipeline_tag: image-classification
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: diabetic-retinopathy-224-procnorm-vit
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. -->
# diabetic-retinopathy-224-procnorm-vit
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the [diabetic retinopathy](https://huggingface.co/datasets/martinezomg/diabetic-retinopathy) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7578
- Accuracy: 0.7431
## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8619 | 1.0 | 50 | 0.8907 | 0.7143 |
| 0.7831 | 2.0 | 100 | 0.7858 | 0.7393 |
| 0.6906 | 3.0 | 150 | 0.7412 | 0.7531 |
| 0.5934 | 4.0 | 200 | 0.7528 | 0.7393 |
| 0.5276 | 5.0 | 250 | 0.7578 | 0.7431 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3 |