metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
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: 0.625
image_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1877
- Accuracy: 0.625
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 1.8317 | 0.2938 |
| No log | 2.0 | 80 | 1.5647 | 0.4437 |
| No log | 3.0 | 120 | 1.4497 | 0.4938 |
| No log | 4.0 | 160 | 1.3529 | 0.5188 |
| No log | 5.0 | 200 | 1.2883 | 0.5125 |
| No log | 6.0 | 240 | 1.2861 | 0.5125 |
| No log | 7.0 | 280 | 1.2655 | 0.55 |
| No log | 8.0 | 320 | 1.2890 | 0.5125 |
| No log | 9.0 | 360 | 1.1955 | 0.575 |
| No log | 10.0 | 400 | 1.2180 | 0.5687 |
| No log | 11.0 | 440 | 1.2835 | 0.55 |
| No log | 12.0 | 480 | 1.2838 | 0.5188 |
| 1.0368 | 13.0 | 520 | 1.2168 | 0.5875 |
| 1.0368 | 14.0 | 560 | 1.1713 | 0.6312 |
| 1.0368 | 15.0 | 600 | 1.2222 | 0.5875 |
| 1.0368 | 16.0 | 640 | 1.3160 | 0.5563 |
| 1.0368 | 17.0 | 680 | 1.2512 | 0.6125 |
| 1.0368 | 18.0 | 720 | 1.3575 | 0.5563 |
| 1.0368 | 19.0 | 760 | 1.3514 | 0.5375 |
| 1.0368 | 20.0 | 800 | 1.3472 | 0.5625 |
| 1.0368 | 21.0 | 840 | 1.3449 | 0.5375 |
| 1.0368 | 22.0 | 880 | 1.3783 | 0.5375 |
| 1.0368 | 23.0 | 920 | 1.3240 | 0.575 |
| 1.0368 | 24.0 | 960 | 1.3391 | 0.5687 |
| 0.2885 | 25.0 | 1000 | 1.3723 | 0.55 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3