metadata
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cards-top_left_swin-tiny-patch4-window7-224-finetuned-dough
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: 0.5874543393374481
cards-top_left_swin-tiny-patch4-window7-224-finetuned-dough
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.9991
- Accuracy: 0.5875
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5983 | 1.0 | 1240 | 1.3399 | 0.4436 |
| 1.5587 | 2.0 | 2481 | 1.3298 | 0.4366 |
| 1.4955 | 3.0 | 3721 | 1.1679 | 0.5129 |
| 1.4884 | 4.0 | 4962 | 1.1331 | 0.5299 |
| 1.4413 | 5.0 | 6202 | 1.1286 | 0.5287 |
| 1.4395 | 6.0 | 7443 | 1.1316 | 0.5226 |
| 1.4497 | 7.0 | 8683 | 1.2127 | 0.4844 |
| 1.3988 | 8.0 | 9924 | 1.1119 | 0.5301 |
| 1.4457 | 9.0 | 11164 | 1.0984 | 0.5389 |
| 1.4153 | 10.0 | 12405 | 1.1226 | 0.5269 |
| 1.3962 | 11.0 | 13645 | 1.0610 | 0.5573 |
| 1.3911 | 12.0 | 14886 | 1.0540 | 0.5595 |
| 1.3617 | 13.0 | 16126 | 1.0646 | 0.5530 |
| 1.3766 | 14.0 | 17367 | 1.0722 | 0.5532 |
| 1.3693 | 15.0 | 18607 | 1.0243 | 0.5721 |
| 1.3624 | 16.0 | 19848 | 1.0212 | 0.5763 |
| 1.3638 | 17.0 | 21088 | 1.0667 | 0.5580 |
| 1.4007 | 18.0 | 22329 | 1.0314 | 0.5730 |
| 1.3415 | 19.0 | 23569 | 1.0191 | 0.5755 |
| 1.3802 | 20.0 | 24810 | 1.0142 | 0.5770 |
| 1.3572 | 21.0 | 26050 | 1.0125 | 0.5771 |
| 1.2962 | 22.0 | 27291 | 1.0167 | 0.5763 |
| 1.2831 | 23.0 | 28531 | 1.0043 | 0.5829 |
| 1.3272 | 24.0 | 29772 | 0.9990 | 0.5858 |
| 1.3197 | 25.0 | 31012 | 1.0033 | 0.5830 |
| 1.3203 | 26.0 | 32253 | 1.0075 | 0.5818 |
| 1.3172 | 27.0 | 33493 | 1.0008 | 0.5852 |
| 1.3197 | 28.0 | 34734 | 1.0016 | 0.5847 |
| 1.2879 | 29.0 | 35974 | 1.0017 | 0.5867 |
| 1.2907 | 29.99 | 37200 | 0.9991 | 0.5875 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2