
<!-- 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
{"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": []}]}
transformers pytorch safetensors vit image-classification generated_from_trainer dataset:martinezomg/diabetic-retinopathy base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #vit #image-classification #generated_from_trainer #dataset-martinezomg/diabetic-retinopathy #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

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



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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 ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #safetensors #vit #image-classification #generated_from_trainer #dataset-martinezomg/diabetic-retinopathy #base_model-google/vit-base-patch16-224-in21k #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.12.0
* Tokenizers 0.13.3