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_fold2
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: 0.46242142661929486
Boya2_SGD_1e3_20Epoch_Swin-large-224_fold2
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: 1.7316
- Accuracy: 0.4624
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 |
|---|---|---|---|---|
| 2.613 | 1.0 | 913 | 2.5089 | 0.2774 |
| 2.2378 | 2.0 | 1826 | 2.3352 | 0.2938 |
| 2.1303 | 3.0 | 2739 | 2.2226 | 0.3184 |
| 2.0563 | 4.0 | 3652 | 2.1385 | 0.3506 |
| 2.1322 | 5.0 | 4565 | 2.0717 | 0.3758 |
| 2.004 | 6.0 | 5478 | 2.0113 | 0.3955 |
| 2.079 | 7.0 | 6391 | 1.9666 | 0.4130 |
| 1.78 | 8.0 | 7304 | 1.9230 | 0.4225 |
| 1.7925 | 9.0 | 8217 | 1.8877 | 0.4354 |
| 1.9366 | 10.0 | 9130 | 1.8567 | 0.4403 |
| 1.5845 | 11.0 | 10043 | 1.8338 | 0.4458 |
| 1.6846 | 12.0 | 10956 | 1.8079 | 0.4520 |
| 1.7316 | 13.0 | 11869 | 1.7920 | 0.4545 |
| 1.6397 | 14.0 | 12782 | 1.7737 | 0.4600 |
| 1.8114 | 15.0 | 13695 | 1.7580 | 0.4605 |
| 1.5862 | 16.0 | 14608 | 1.7502 | 0.4621 |
| 1.8464 | 17.0 | 15521 | 1.7422 | 0.4641 |
| 1.8008 | 18.0 | 16434 | 1.7370 | 0.4627 |
| 1.719 | 19.0 | 17347 | 1.7333 | 0.4632 |
| 1.5652 | 20.0 | 18260 | 1.7316 | 0.4624 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.21.0
- Tokenizers 0.13.2