metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
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: 0.48125
results
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: 1.3523
- Accuracy: 0.4813
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|
| 2.093 | 1.0 | 10 | 1.8451 | 0.3312 |
| 1.4651 | 2.0 | 20 | 1.6375 | 0.3812 |
| 1.033 | 3.0 | 30 | 1.5209 | 0.3875 |
| 0.7164 | 4.0 | 40 | 1.4455 | 0.4375 |
| 0.4719 | 5.0 | 50 | 1.3971 | 0.425 |
| 0.3109 | 6.0 | 60 | 1.3746 | 0.475 |
| 0.2034 | 7.0 | 70 | 1.3600 | 0.45 |
| 0.1403 | 8.0 | 80 | 1.3523 | 0.4813 |
| 0.1074 | 9.0 | 90 | 1.3493 | 0.4813 |
| 0.0931 | 10.0 | 100 | 1.3471 | 0.475 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1