metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dinov2-small-finetuned-papsmear
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: 0.8602941176470589
dinov2-small-finetuned-papsmear
This model is a fine-tuned version of facebook/dinov2-small on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3843
- Accuracy: 0.8603
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.846 | 0.9935 | 38 | 1.0217 | 0.5956 |
| 1.0241 | 1.9869 | 76 | 0.8413 | 0.6544 |
| 0.9178 | 2.9804 | 114 | 0.7204 | 0.7426 |
| 0.693 | 4.0 | 153 | 0.5731 | 0.75 |
| 0.7157 | 4.9935 | 191 | 0.5501 | 0.8162 |
| 0.5006 | 5.9869 | 229 | 0.6096 | 0.7794 |
| 0.4576 | 6.9804 | 267 | 0.5535 | 0.7941 |
| 0.467 | 8.0 | 306 | 0.5041 | 0.8162 |
| 0.4378 | 8.9935 | 344 | 0.5771 | 0.8015 |
| 0.2876 | 9.9869 | 382 | 0.4234 | 0.8456 |
| 0.2308 | 10.9804 | 420 | 0.4946 | 0.8382 |
| 0.2312 | 12.0 | 459 | 0.5098 | 0.8309 |
| 0.1625 | 12.9935 | 497 | 0.3813 | 0.8603 |
| 0.1775 | 13.9869 | 535 | 0.3695 | 0.8529 |
| 0.1358 | 14.9020 | 570 | 0.3843 | 0.8603 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1