|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: facebook/dinov2-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- image_folder |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: dinov2-base-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: 0.9556772908366534 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# dinov2-base-finetuned-SkinDisease |
|
|
|
|
|
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the image_folder dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1321 |
|
|
- Accuracy: 0.9557 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
|
| 0.9599 | 1.0 | 282 | 0.6866 | 0.7811 | |
|
|
| 0.6176 | 2.0 | 565 | 0.4806 | 0.8399 | |
|
|
| 0.4614 | 3.0 | 847 | 0.3092 | 0.8934 | |
|
|
| 0.3976 | 4.0 | 1130 | 0.2620 | 0.9141 | |
|
|
| 0.3606 | 5.0 | 1412 | 0.2514 | 0.9208 | |
|
|
| 0.3075 | 6.0 | 1695 | 0.1968 | 0.9320 | |
|
|
| 0.2152 | 7.0 | 1977 | 0.2004 | 0.9377 | |
|
|
| 0.2194 | 8.0 | 2260 | 0.1627 | 0.9442 | |
|
|
| 0.1706 | 9.0 | 2542 | 0.1449 | 0.9500 | |
|
|
| 0.172 | 9.98 | 2820 | 0.1321 | 0.9557 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.33.2 |
|
|
- Pytorch 2.0.0 |
|
|
- Datasets 2.1.0 |
|
|
- Tokenizers 0.13.3 |
|
|
|
