metadata
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-skindiseaseicthuawei25
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: 0.9693806541405706
ky-finetuned-skindiseaseicthuawei25
This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1010
- Accuracy: 0.9694
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 |
|---|---|---|---|---|
| 1.5505 | 1.0 | 203 | 0.8481 | 0.7397 |
| 0.7314 | 2.0 | 406 | 0.3937 | 0.8852 |
| 0.5221 | 3.0 | 609 | 0.3209 | 0.9057 |
| 0.4238 | 4.0 | 812 | 0.2358 | 0.9283 |
| 0.3587 | 5.0 | 1015 | 0.1692 | 0.9495 |
| 0.2975 | 6.0 | 1218 | 0.1708 | 0.9468 |
| 0.2536 | 7.0 | 1421 | 0.1420 | 0.9593 |
| 0.2198 | 8.0 | 1624 | 0.1231 | 0.9631 |
| 0.1793 | 9.0 | 1827 | 0.1094 | 0.9687 |
| 0.1538 | 9.9543 | 2020 | 0.1010 | 0.9694 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0