metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.50625
image_classification
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: 1.2697
- Accuracy: 0.5062
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.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 |
|---|---|---|---|---|
| 2.5374 | 1.0 | 10 | 2.2324 | 0.1688 |
| 1.9423 | 2.0 | 20 | 1.8484 | 0.35 |
| 1.6386 | 3.0 | 30 | 1.8398 | 0.3312 |
| 1.3437 | 4.0 | 40 | 1.4253 | 0.475 |
| 1.1703 | 5.0 | 50 | 1.4136 | 0.4625 |
| 1.0267 | 6.0 | 60 | 1.3867 | 0.4562 |
| 0.8702 | 7.0 | 70 | 1.2915 | 0.525 |
| 0.7696 | 8.0 | 80 | 1.2238 | 0.5687 |
| 0.6327 | 9.0 | 90 | 1.2732 | 0.5312 |
| 0.5017 | 10.0 | 100 | 1.2810 | 0.5188 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0