---
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Psoriasis-M-vit-large-patch16-224-in21k
  results: []
pipeline_tag: image-classification
---

<!-- 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. -->

# Psoriasis-M-vit-large-patch16-224-in21k

This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1464
- Accuracy: 0.9792

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.1103          | 0.6667   |
| 1.4249        | 2.0   | 13   | 0.5429          | 0.875    |
| 1.4249        | 2.92  | 19   | 0.3529          | 0.9167   |
| 0.3823        | 4.0   | 26   | 0.2861          | 0.9375   |
| 0.1072        | 4.62  | 30   | 0.2801          | 0.9375   |
| No log        | 0.92  | 6    | 0.2647          | 0.9167   |
| 0.0527        | 2.0   | 13   | 0.1843          | 0.9792   |
| 0.0527        | 2.92  | 19   | 0.1604          | 0.9792   |
| 0.0138        | 4.0   | 26   | 0.1480          | 0.9792   |
| 0.0074        | 4.62  | 30   | 0.1464          | 0.9792   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2