metadata
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: []
diabetic-retinopathy-224-procnorm-vit
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the 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