|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/dinov2-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: ky-finetuned-skindiseaseicthuawei32 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9622508792497069 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ky-finetuned-skindiseaseicthuawei32 |
|
|
|
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1058 |
|
- Accuracy: 0.9623 |
|
|
|
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.3894 | 1.0 | 300 | 0.6160 | 0.8061 | |
|
| 0.6543 | 2.0 | 600 | 0.4378 | 0.8635 | |
|
| 0.471 | 3.0 | 900 | 0.2566 | 0.9161 | |
|
| 0.3853 | 4.0 | 1200 | 0.2498 | 0.9135 | |
|
| 0.3225 | 5.0 | 1500 | 0.2157 | 0.9290 | |
|
| 0.2769 | 6.0 | 1800 | 0.1747 | 0.9407 | |
|
| 0.2364 | 7.0 | 2100 | 0.1502 | 0.9487 | |
|
| 0.2005 | 8.0 | 2400 | 0.1282 | 0.9547 | |
|
| 0.1737 | 9.0 | 2700 | 0.1129 | 0.9597 | |
|
| 0.1468 | 10.0 | 3000 | 0.1058 | 0.9623 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.0 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
