metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: camera-type
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: 0.9915611814345991
camera-type
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: 0.0235
- Accuracy: 0.9916
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: 0.0001
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0064 | 0.4 | 200 | 0.0235 | 0.9916 |
| 0.0034 | 0.79 | 400 | 0.0392 | 0.9941 |
| 0.0066 | 1.19 | 600 | 0.1011 | 0.9840 |
| 0.0 | 1.58 | 800 | 0.1227 | 0.9840 |
| 0.0 | 1.98 | 1000 | 0.1232 | 0.9840 |
| 0.0 | 2.37 | 1200 | 0.1433 | 0.9840 |
| 0.0 | 2.77 | 1400 | 0.1416 | 0.9840 |
| 0.0 | 3.16 | 1600 | 0.1408 | 0.9840 |
| 0.0 | 3.56 | 1800 | 0.1401 | 0.9840 |
| 0.0 | 3.95 | 2000 | 0.1394 | 0.9840 |
| 0.0 | 4.35 | 2200 | 0.1390 | 0.9840 |
| 0.0 | 4.74 | 2400 | 0.1389 | 0.9840 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3