metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vit_base_patch16_224-finetuned-SkinDisease
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9342629482071713
vit_base_patch16_224-finetuned-SkinDisease
This model is a fine-tuned version of google/vit-base-patch16-224 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1992
- Accuracy: 0.9343
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|---|---|---|---|---|
| 0.9099 | 1.0 | 282 | 0.8248 | 0.7647 |
| 0.5848 | 2.0 | 565 | 0.4236 | 0.8748 |
| 0.3952 | 3.0 | 847 | 0.3154 | 0.9021 |
| 0.3957 | 4.0 | 1130 | 0.2695 | 0.9106 |
| 0.3146 | 5.0 | 1412 | 0.2381 | 0.9198 |
| 0.2883 | 6.0 | 1695 | 0.2407 | 0.9218 |
| 0.2264 | 7.0 | 1977 | 0.2160 | 0.9278 |
| 0.2339 | 8.0 | 2260 | 0.2121 | 0.9283 |
| 0.1966 | 9.0 | 2542 | 0.2044 | 0.9303 |
| 0.2366 | 9.98 | 2820 | 0.1992 | 0.9343 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3