metadata
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
dinov2-base-finetuned-SkinDisease
This model is a fine-tuned version of 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