metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-U8-10
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8833333333333333
vit-base-patch16-224-U8-10
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5606
- Accuracy: 0.8833
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: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.2473 | 1.0 | 20 | 1.1804 | 0.5833 |
0.9555 | 2.0 | 40 | 0.9370 | 0.65 |
0.727 | 3.0 | 60 | 0.7202 | 0.6833 |
0.5288 | 4.0 | 80 | 0.5606 | 0.8833 |
0.3876 | 5.0 | 100 | 0.6482 | 0.7667 |
0.296 | 6.0 | 120 | 0.7458 | 0.7167 |
0.236 | 7.0 | 140 | 0.4677 | 0.8833 |
0.2129 | 8.0 | 160 | 0.5138 | 0.8333 |
0.1781 | 9.0 | 180 | 0.4736 | 0.85 |
0.1854 | 10.0 | 200 | 0.4801 | 0.8 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0