metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: dinov2-base-finetuned-eye
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: 0.968
- name: F1
type: f1
value: 0.9678344915175675
dinov2-base-finetuned-eye
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: 0.2262
- Accuracy: 0.968
- F1: 0.9678
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | F1 |
|---|---|---|---|---|---|
| 0.3853 | 1.0 | 250 | 0.4918 | 0.874 | 0.8729 |
| 0.5345 | 2.0 | 500 | 0.4390 | 0.878 | 0.8771 |
| 0.4693 | 3.0 | 750 | 0.3857 | 0.88 | 0.8796 |
| 0.1933 | 4.0 | 1000 | 0.3444 | 0.894 | 0.8948 |
| 0.3146 | 5.0 | 1250 | 0.2456 | 0.936 | 0.9362 |
| 0.1832 | 6.0 | 1500 | 0.3369 | 0.924 | 0.9229 |
| 0.1407 | 7.0 | 1750 | 0.3425 | 0.946 | 0.9454 |
| 0.1462 | 8.0 | 2000 | 0.2864 | 0.948 | 0.9476 |
| 0.0905 | 9.0 | 2250 | 0.2177 | 0.956 | 0.9560 |
| 0.0859 | 10.0 | 2500 | 0.2262 | 0.968 | 0.9678 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0