metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.5625
image_classification
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: 1.2259
- Accuracy: 0.5625
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8751 | 1.0 | 20 | 1.7512 | 0.3 |
| 1.3825 | 2.0 | 40 | 1.4946 | 0.425 |
| 1.1532 | 3.0 | 60 | 1.3387 | 0.45 |
| 0.9865 | 4.0 | 80 | 1.3469 | 0.4562 |
| 0.8767 | 5.0 | 100 | 1.2275 | 0.55 |
| 0.7586 | 6.0 | 120 | 1.2560 | 0.5062 |
| 0.5985 | 7.0 | 140 | 1.2596 | 0.5062 |
| 0.5052 | 8.0 | 160 | 1.3010 | 0.5687 |
| 0.4243 | 9.0 | 180 | 1.2613 | 0.5563 |
| 0.387 | 10.0 | 200 | 1.2750 | 0.5312 |
| 0.3529 | 11.0 | 220 | 1.3103 | 0.55 |
| 0.218 | 12.0 | 240 | 1.1832 | 0.55 |
| 0.2428 | 13.0 | 260 | 1.2527 | 0.5563 |
| 0.2399 | 14.0 | 280 | 1.4836 | 0.5375 |
| 0.218 | 15.0 | 300 | 1.4056 | 0.4875 |
| 0.1784 | 16.0 | 320 | 1.3879 | 0.5563 |
| 0.2021 | 17.0 | 340 | 1.4346 | 0.5375 |
| 0.1342 | 18.0 | 360 | 1.4666 | 0.4813 |
| 0.1499 | 19.0 | 380 | 1.4104 | 0.5687 |
| 0.1032 | 20.0 | 400 | 1.5402 | 0.525 |
| 0.1214 | 21.0 | 420 | 1.4114 | 0.55 |
| 0.153 | 22.0 | 440 | 1.5887 | 0.525 |
| 0.1276 | 23.0 | 460 | 1.4588 | 0.5188 |
| 0.1114 | 24.0 | 480 | 1.4866 | 0.5312 |
| 0.1305 | 25.0 | 500 | 1.4203 | 0.5687 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1