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-ve-U10-12
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: 0.7254901960784313
vit-base-patch16-224-ve-U10-12
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: 0.7451
- Accuracy: 0.7255
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: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3659 | 0.97 | 15 | 1.2287 | 0.4706 |
| 1.1063 | 2.0 | 31 | 1.0234 | 0.6863 |
| 0.9468 | 2.97 | 46 | 0.8665 | 0.6863 |
| 0.6825 | 4.0 | 62 | 0.7482 | 0.7059 |
| 0.5534 | 4.97 | 77 | 0.7609 | 0.7059 |
| 0.4019 | 6.0 | 93 | 0.7092 | 0.7255 |
| 0.3323 | 6.97 | 108 | 0.6623 | 0.7843 |
| 0.2743 | 8.0 | 124 | 0.7407 | 0.7059 |
| 0.2411 | 8.97 | 139 | 0.6249 | 0.7647 |
| 0.2021 | 10.0 | 155 | 0.7222 | 0.7451 |
| 0.1925 | 10.97 | 170 | 0.7808 | 0.7059 |
| 0.1748 | 11.61 | 180 | 0.7451 | 0.7255 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0