metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cifar100
metrics:
- accuracy
model-index:
- name: swin-tiny-finetuned-cifar100
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: cifar100
type: cifar100
args: cifar100
metrics:
- name: Accuracy
type: accuracy
value: 0.8735
swin-tiny-finetuned-cifar100
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4223
- Accuracy: 0.8735
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20 (with early stopping)
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.6439 | 1.0 | 781 | 0.8138 | 0.6126 |
| 0.6222 | 2.0 | 1562 | 0.8393 | 0.5094 |
| 0.2912 | 3.0 | 2343 | 0.861 | 0.4452 |
| 0.2234 | 4.0 | 3124 | 0.8679 | 0.4330 |
| 0.121 | 5.0 | 3905 | 0.8735 | 0.4223 |
| 0.2589 | 6.0 | 4686 | 0.8622 | 0.4775 |
| 0.1419 | 7.0 | 5467 | 0.8642 | 0.4900 |
| 0.1513 | 8.0 | 6248 | 0.8667 | 0.4956 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1