|
--- |
|
license: apache-2.0 |
|
base_model: microsoft/swin-tiny-patch4-window7-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: cards_bottom_left_swin-tiny-patch4-window7-224-finetuned-v2_more_Data |
|
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: 0.5927874941959449 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# cards_bottom_left_swin-tiny-patch4-window7-224-finetuned-v2_more_Data |
|
|
|
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.0009 |
|
- Accuracy: 0.5928 |
|
|
|
## 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: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 1.559 | 1.0 | 1362 | 1.3402 | 0.4189 | |
|
| 1.5165 | 2.0 | 2725 | 1.2308 | 0.4647 | |
|
| 1.484 | 3.0 | 4087 | 1.1676 | 0.4954 | |
|
| 1.5037 | 4.0 | 5450 | 1.1206 | 0.5198 | |
|
| 1.4489 | 5.0 | 6812 | 1.1162 | 0.5284 | |
|
| 1.4335 | 6.0 | 8175 | 1.1395 | 0.5047 | |
|
| 1.4281 | 7.0 | 9537 | 1.0606 | 0.5445 | |
|
| 1.4219 | 8.0 | 10900 | 1.0754 | 0.5408 | |
|
| 1.3935 | 9.0 | 12262 | 1.0285 | 0.5604 | |
|
| 1.3542 | 10.0 | 13625 | 1.0497 | 0.5453 | |
|
| 1.3761 | 11.0 | 14987 | 1.0535 | 0.5450 | |
|
| 1.3824 | 12.0 | 16350 | 1.0268 | 0.5591 | |
|
| 1.3709 | 13.0 | 17712 | 1.0015 | 0.5690 | |
|
| 1.3361 | 14.0 | 19075 | 1.0266 | 0.5595 | |
|
| 1.3673 | 15.0 | 20437 | 0.9988 | 0.5772 | |
|
| 1.376 | 16.0 | 21800 | 0.9950 | 0.5744 | |
|
| 1.3486 | 17.0 | 23162 | 0.9837 | 0.5784 | |
|
| 1.3333 | 18.0 | 24525 | 0.9771 | 0.5827 | |
|
| 1.347 | 19.0 | 25887 | 0.9895 | 0.5770 | |
|
| 1.3381 | 20.0 | 27250 | 0.9709 | 0.5820 | |
|
| 1.3385 | 21.0 | 28612 | 0.9704 | 0.5833 | |
|
| 1.336 | 22.0 | 29975 | 0.9646 | 0.5885 | |
|
| 1.3372 | 23.0 | 31337 | 0.9653 | 0.5879 | |
|
| 1.2979 | 24.0 | 32700 | 0.9867 | 0.5814 | |
|
| 1.2948 | 25.0 | 34062 | 0.9633 | 0.5870 | |
|
| 1.2767 | 26.0 | 35425 | 0.9578 | 0.5877 | |
|
| 1.3012 | 27.0 | 36787 | 0.9709 | 0.5867 | |
|
| 1.2667 | 28.0 | 38150 | 0.9648 | 0.5899 | |
|
| 1.3 | 29.0 | 39512 | 0.9560 | 0.5930 | |
|
| 1.2735 | 30.0 | 40875 | 0.9595 | 0.5949 | |
|
| 1.2895 | 31.0 | 42237 | 0.9851 | 0.5809 | |
|
| 1.2234 | 32.0 | 43600 | 0.9601 | 0.5931 | |
|
| 1.2212 | 33.0 | 44962 | 0.9800 | 0.5917 | |
|
| 1.2483 | 34.0 | 46325 | 0.9662 | 0.5982 | |
|
| 1.2507 | 35.0 | 47687 | 0.9657 | 0.5910 | |
|
| 1.2539 | 36.0 | 49050 | 0.9954 | 0.5783 | |
|
| 1.2491 | 37.0 | 50412 | 0.9718 | 0.5924 | |
|
| 1.2397 | 38.0 | 51775 | 0.9769 | 0.5930 | |
|
| 1.1903 | 39.0 | 53137 | 0.9717 | 0.5945 | |
|
| 1.2475 | 40.0 | 54500 | 0.9995 | 0.5855 | |
|
| 1.2371 | 41.0 | 55862 | 0.9861 | 0.5935 | |
|
| 1.2561 | 42.0 | 57225 | 0.9856 | 0.5958 | |
|
| 1.2069 | 43.0 | 58587 | 0.9913 | 0.5892 | |
|
| 1.2188 | 44.0 | 59950 | 0.9902 | 0.5950 | |
|
| 1.1732 | 45.0 | 61312 | 0.9892 | 0.5949 | |
|
| 1.1705 | 46.0 | 62675 | 0.9991 | 0.5914 | |
|
| 1.18 | 47.0 | 64037 | 0.9952 | 0.5925 | |
|
| 1.2353 | 48.0 | 65400 | 0.9999 | 0.5933 | |
|
| 1.2057 | 49.0 | 66762 | 1.0001 | 0.5920 | |
|
| 1.1833 | 49.98 | 68100 | 1.0009 | 0.5928 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
