metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-blur
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: blurryimages
type: blurryimages
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
vit-base-blur
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on a blurry images dataset. It achieves the following results on the evaluation set:
- Loss: 0.0007
- Accuracy: 1.0
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0027 | 2.27 | 100 | 0.0565 | 0.9870 |
| 0.0013 | 4.55 | 200 | 0.0012 | 1.0 |
| 0.0008 | 6.82 | 300 | 0.0008 | 1.0 |
| 0.0007 | 9.09 | 400 | 0.0007 | 1.0 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3