metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cifar100
metrics:
- accuracy
model-index:
- name: swin-small-finetuned-cifar100
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: cifar100
type: cifar100
args: cifar100
metrics:
- name: Accuracy
type: accuracy
value: 0.8938
swin-small-finetuned-cifar100
This model is a fine-tuned version of microsoft/swin-small-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6281
- Accuracy: 0.8938
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.72 | 1.0 | 781 | 0.6691 | 0.8077 |
| 0.6944 | 2.0 | 1562 | 0.4797 | 0.8495 |
| 0.2794 | 3.0 | 2343 | 0.4338 | 0.869 |
| 0.2569 | 4.0 | 3124 | 0.4263 | 0.879 |
| 0.1417 | 5.0 | 3905 | 0.4385 | 0.8819 |
| 0.0961 | 6.0 | 4686 | 0.4720 | 0.8854 |
| 0.0584 | 7.0 | 5467 | 0.4941 | 0.885 |
| 0.0351 | 8.0 | 6248 | 0.5253 | 0.885 |
| 0.0107 | 9.0 | 7029 | 0.5598 | 0.8887 |
| 0.0118 | 10.0 | 7810 | 0.5998 | 0.8858 |
| 0.0097 | 11.0 | 8591 | 0.5957 | 0.8941 |
| 0.0044 | 12.0 | 9372 | 0.6237 | 0.8912 |
| 0.0013 | 13.0 | 10153 | 0.6286 | 0.8929 |
| 0.0102 | 14.0 | 10934 | 0.6281 | 0.8938 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1