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-skindiseasefinal
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: 0.9552567237163814
ky-finetuned-skindiseasefinal
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: 0.1301
- Accuracy: 0.9553
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 |
|---|---|---|---|---|
| 1.4949 | 0.9974 | 287 | 0.6912 | 0.7770 |
| 0.7268 | 1.9974 | 574 | 0.3927 | 0.8775 |
| 0.5179 | 2.9974 | 861 | 0.3185 | 0.8983 |
| 0.4193 | 3.9974 | 1148 | 0.2439 | 0.9191 |
| 0.3576 | 4.9974 | 1435 | 0.2107 | 0.9301 |
| 0.3015 | 5.9974 | 1722 | 0.1821 | 0.9386 |
| 0.2648 | 6.9974 | 2009 | 0.1685 | 0.9411 |
| 0.2228 | 7.9974 | 2296 | 0.1497 | 0.9487 |
| 0.1946 | 8.9974 | 2583 | 0.1407 | 0.9494 |
| 0.1625 | 9.9974 | 2870 | 0.1301 | 0.9553 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0