metadata
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: finetuned-SwinT-Indian-Food-Classification-v1
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: Indian-Food-Images
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9373007438894793
finetuned-SwinT-Indian-Food-Classification-v1
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the Indian-Food-Images dataset. It achieves the following results on the evaluation set:
- Loss: 0.2868
- Accuracy: 0.9373
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: 16
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2433 | 0.3 | 100 | 0.7067 | 0.8193 |
| 0.6458 | 0.6 | 200 | 0.4692 | 0.8789 |
| 0.635 | 0.9 | 300 | 0.4864 | 0.8682 |
| 0.6219 | 1.2 | 400 | 0.4240 | 0.8831 |
| 0.4889 | 1.5 | 500 | 0.3840 | 0.8948 |
| 0.2963 | 1.8 | 600 | 0.4279 | 0.8959 |
| 0.4405 | 2.1 | 700 | 0.3508 | 0.9118 |
| 0.3803 | 2.4 | 800 | 0.3659 | 0.9086 |
| 0.3499 | 2.7 | 900 | 0.3347 | 0.9214 |
| 0.3131 | 3.0 | 1000 | 0.2910 | 0.9277 |
| 0.3036 | 3.3 | 1100 | 0.3938 | 0.9107 |
| 0.2697 | 3.6 | 1200 | 0.3566 | 0.9171 |
| 0.1551 | 3.9 | 1300 | 0.3369 | 0.9341 |
| 0.0752 | 4.2 | 1400 | 0.2868 | 0.9373 |
| 0.132 | 4.5 | 1500 | 0.3023 | 0.9373 |
| 0.1133 | 4.8 | 1600 | 0.2978 | 0.9416 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1