metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: dresses
results:
- task:
type: image-classification
name: Image Classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- type: accuracy
value: 0.9013840830449827
name: Accuracy
dresses
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: 0.4588
- Accuracy: 0.9014
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: 0.0002
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2458 | 1.23 | 100 | 0.4519 | 0.8633 |
| 0.0937 | 2.47 | 200 | 0.4285 | 0.8754 |
| 0.0802 | 3.7 | 300 | 0.4683 | 0.8754 |
| 0.041 | 4.94 | 400 | 0.4088 | 0.9031 |
| 0.0277 | 6.17 | 500 | 0.3979 | 0.8945 |
| 0.0459 | 7.41 | 600 | 0.4253 | 0.9014 |
| 0.024 | 8.64 | 700 | 0.4680 | 0.8893 |
| 0.0267 | 9.88 | 800 | 0.4575 | 0.8945 |
| 0.019 | 11.11 | 900 | 0.4470 | 0.8893 |
| 0.0235 | 12.35 | 1000 | 0.4380 | 0.9066 |
| 0.0129 | 13.58 | 1100 | 0.4557 | 0.9048 |
| 0.0211 | 14.81 | 1200 | 0.4588 | 0.9014 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1