metadata
license: apache-2.0
base_model: microsoft/swin-large-patch4-window7-224-in22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_SGD_1e3_20Epoch_Swin-large-224_fold3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.4703308722996992
Boya2_SGD_1e3_20Epoch_Swin-large-224_fold3
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7253
- Accuracy: 0.4703
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|---|---|---|---|---|
| 2.4987 | 1.0 | 913 | 2.4779 | 0.2773 |
| 2.2499 | 2.0 | 1826 | 2.3076 | 0.2986 |
| 2.1231 | 3.0 | 2739 | 2.2022 | 0.3325 |
| 2.1706 | 4.0 | 3652 | 2.1236 | 0.3672 |
| 2.0969 | 5.0 | 4565 | 2.0581 | 0.3940 |
| 1.9524 | 6.0 | 5478 | 2.0029 | 0.4085 |
| 1.9868 | 7.0 | 6391 | 1.9548 | 0.4208 |
| 1.9729 | 8.0 | 7304 | 1.9129 | 0.4293 |
| 1.9817 | 9.0 | 8217 | 1.8827 | 0.4331 |
| 1.9117 | 10.0 | 9130 | 1.8505 | 0.4430 |
| 1.8805 | 11.0 | 10043 | 1.8244 | 0.4482 |
| 1.8198 | 12.0 | 10956 | 1.8053 | 0.4528 |
| 1.7002 | 13.0 | 11869 | 1.7829 | 0.4558 |
| 1.811 | 14.0 | 12782 | 1.7721 | 0.4602 |
| 1.8637 | 15.0 | 13695 | 1.7553 | 0.4602 |
| 1.8566 | 16.0 | 14608 | 1.7454 | 0.4654 |
| 1.742 | 17.0 | 15521 | 1.7350 | 0.4665 |
| 1.692 | 18.0 | 16434 | 1.7303 | 0.4695 |
| 1.8241 | 19.0 | 17347 | 1.7261 | 0.4695 |
| 1.8203 | 20.0 | 18260 | 1.7253 | 0.4703 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.21.0
- Tokenizers 0.13.2