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---
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Psoriasis-Aug-M2-vit-large-patch16-224-in21k
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. -->
# Psoriasis-Aug-M2-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: 0.0268
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4421 | 0.99 | 36 | 0.2504 | 0.8958 |
| 0.0968 | 1.99 | 72 | 0.0631 | 0.9583 |
| 0.0321 | 2.98 | 108 | 0.0639 | 0.9792 |
| 0.0065 | 4.0 | 145 | 0.0234 | 1.0 |
| 0.0067 | 4.97 | 180 | 0.0268 | 0.9792 |
### Test results
| Classes | precision | recall | f1-score | support|
|:-------------------:|:---------:|:------:|:--------:|:------:|
| Erythromelal | 1.00 | 1.00 | 1.00 | 5 |
| Guttate | 1.00 | 1.00 | 1.00 | 7 |
| Inverse | 1.00 | 1.00 | 1.00 | 4 |
| Nail | 1.00 | 1.00 | 1.00 | 10 |
| Normal | 1.00 | 1.00 | 1.00 | 11 |
| Plaque | 1.00 | 1.00 | 1.00 | 10 |
| Psoriatic Arthritis | 1.00 | 1.00 | 1.00 | 6 |
| Pustular | 1.00 | 1.00 | 1.00 | 6 |
| | | | | |
| accuracy | | | 1.00 | 59|
| macro avg | 1.00 | 1.00 | 1.00 | 59 |
| weighted avg | 1.00 | 1.00 | 1.00 | 59 |
### confusion Matrix results
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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