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---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224-pt22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Psoriasis-500-100aug-224-beit-large
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7991266375545851
---
<!-- 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-500-100aug-224-beit-large
This model is a fine-tuned version of [microsoft/beit-large-patch16-224-pt22k](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1823
- Accuracy: 0.7991
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8236 | 0.9973 | 92 | 1.1536 | 0.6358 |
| 0.4282 | 1.9946 | 184 | 0.8848 | 0.7389 |
| 0.2305 | 2.9919 | 276 | 0.9811 | 0.7258 |
| 0.1206 | 4.0 | 369 | 0.8858 | 0.7808 |
| 0.1107 | 4.9973 | 461 | 1.1129 | 0.7397 |
| 0.0319 | 5.9946 | 553 | 1.1625 | 0.7703 |
| 0.0073 | 6.9919 | 645 | 1.1938 | 0.7895 |
| 0.0078 | 8.0 | 738 | 1.3031 | 0.7790 |
| 0.0013 | 8.9973 | 830 | 1.2117 | 0.7974 |
| 0.002 | 9.9729 | 920 | 1.1823 | 0.7991 |
# Classification Report
| Class | Precision (%) | Recall (%) | F1-Score (%) | Support |
|---------------------|---------------|------------|--------------|---------|
| Abnormal | 66 | 62 | 64 | 108 |
| Erythrodermic | 96 | 76 | 85 | 100 |
| Guttate | 95 | 83 | 89 | 114 |
| Inverse | 83 | 91 | 87 | 108 |
| Nail | 81 | 84 | 83 | 99 |
| Normal | 81 | 79 | 80 | 82 |
| Not Define | 98 | 95 | 96 | 92 |
| Palm Soles | 82 | 88 | 85 | 102 |
| Plaque | 70 | 88 | 78 | 84 |
| Psoriatic Arthritis | 78 | 74 | 76 | 104 |
| Pustular | 71 | 76 | 74 | 112 |
| Scalp | 84 | 86 | 85 | 80 |
| **Accuracy** | | | **82** | 1185 |
| **Macro Avg** | **82** | **82** | **82** | 1185 |
| **Weighted Avg** | **82** | **82** | **82** | 1185 |
---
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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