|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: swin-tiny-patch4-window7-224-finetuned-woody_LeftGR_clean_130epochs |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8888888888888888 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# swin-tiny-patch4-window7-224-finetuned-woody_LeftGR_clean_130epochs |
|
|
|
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: 0.5224 |
|
- Accuracy: 0.8889 |
|
|
|
## 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: 130 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 0.6569 | 0.99 | 52 | 0.6227 | 0.6720 | |
|
| 0.6069 | 1.99 | 104 | 0.5891 | 0.6934 | |
|
| 0.6044 | 2.99 | 156 | 0.5543 | 0.7202 | |
|
| 0.5898 | 3.99 | 208 | 0.5440 | 0.7229 | |
|
| 0.5774 | 4.99 | 260 | 0.5360 | 0.7282 | |
|
| 0.5912 | 5.99 | 312 | 0.5466 | 0.7189 | |
|
| 0.5685 | 6.99 | 364 | 0.5184 | 0.7336 | |
|
| 0.5604 | 7.99 | 416 | 0.5138 | 0.7550 | |
|
| 0.5455 | 8.99 | 468 | 0.5157 | 0.7376 | |
|
| 0.5462 | 9.99 | 520 | 0.5078 | 0.7657 | |
|
| 0.5729 | 10.99 | 572 | 0.4957 | 0.7523 | |
|
| 0.5555 | 11.99 | 624 | 0.5016 | 0.7564 | |
|
| 0.5291 | 12.99 | 676 | 0.5665 | 0.7323 | |
|
| 0.524 | 13.99 | 728 | 0.5431 | 0.7390 | |
|
| 0.5194 | 14.99 | 780 | 0.5019 | 0.7430 | |
|
| 0.5368 | 15.99 | 832 | 0.4810 | 0.7724 | |
|
| 0.4917 | 16.99 | 884 | 0.4793 | 0.7711 | |
|
| 0.4892 | 17.99 | 936 | 0.4981 | 0.7631 | |
|
| 0.5117 | 18.99 | 988 | 0.4969 | 0.7510 | |
|
| 0.5033 | 19.99 | 1040 | 0.4711 | 0.7671 | |
|
| 0.4807 | 20.99 | 1092 | 0.4959 | 0.7724 | |
|
| 0.493 | 21.99 | 1144 | 0.4509 | 0.7898 | |
|
| 0.4887 | 22.99 | 1196 | 0.4791 | 0.7738 | |
|
| 0.4517 | 23.99 | 1248 | 0.4722 | 0.7831 | |
|
| 0.4617 | 24.99 | 1300 | 0.4344 | 0.7992 | |
|
| 0.4609 | 25.99 | 1352 | 0.4647 | 0.7952 | |
|
| 0.4365 | 26.99 | 1404 | 0.4459 | 0.7912 | |
|
| 0.4515 | 27.99 | 1456 | 0.5217 | 0.7644 | |
|
| 0.4538 | 28.99 | 1508 | 0.4375 | 0.8166 | |
|
| 0.4371 | 29.99 | 1560 | 0.4406 | 0.8005 | |
|
| 0.4228 | 30.99 | 1612 | 0.4383 | 0.7912 | |
|
| 0.4347 | 31.99 | 1664 | 0.4246 | 0.8153 | |
|
| 0.4354 | 32.99 | 1716 | 0.4606 | 0.8112 | |
|
| 0.4194 | 33.99 | 1768 | 0.4371 | 0.8112 | |
|
| 0.4073 | 34.99 | 1820 | 0.4436 | 0.8126 | |
|
| 0.3935 | 35.99 | 1872 | 0.4255 | 0.8273 | |
|
| 0.3862 | 36.99 | 1924 | 0.4054 | 0.8233 | |
|
| 0.3739 | 37.99 | 1976 | 0.4206 | 0.8126 | |
|
| 0.3794 | 38.99 | 2028 | 0.4075 | 0.8220 | |
|
| 0.3713 | 39.99 | 2080 | 0.3787 | 0.8353 | |
|
| 0.3901 | 40.99 | 2132 | 0.3840 | 0.8246 | |
|
| 0.3514 | 41.99 | 2184 | 0.4136 | 0.8367 | |
|
| 0.3718 | 42.99 | 2236 | 0.3867 | 0.8394 | |
|
| 0.3699 | 43.99 | 2288 | 0.3737 | 0.8487 | |
|
| 0.3314 | 44.99 | 2340 | 0.3756 | 0.8527 | |
|
| 0.3167 | 45.99 | 2392 | 0.4211 | 0.8474 | |
|
| 0.301 | 46.99 | 2444 | 0.3870 | 0.8434 | |
|
| 0.3048 | 47.99 | 2496 | 0.4236 | 0.8461 | |
|
| 0.2735 | 48.99 | 2548 | 0.4122 | 0.8380 | |
|
| 0.3003 | 49.99 | 2600 | 0.3609 | 0.8568 | |
|
| 0.3147 | 50.99 | 2652 | 0.4258 | 0.8367 | |
|
| 0.288 | 51.99 | 2704 | 0.3855 | 0.8394 | |
|
| 0.2895 | 52.99 | 2756 | 0.3543 | 0.8527 | |
|
| 0.2685 | 53.99 | 2808 | 0.3668 | 0.8541 | |
|
| 0.2931 | 54.99 | 2860 | 0.3565 | 0.8541 | |
|
| 0.2966 | 55.99 | 2912 | 0.3985 | 0.8568 | |
|
| 0.2737 | 56.99 | 2964 | 0.4100 | 0.8581 | |
|
| 0.2892 | 57.99 | 3016 | 0.3480 | 0.8768 | |
|
| 0.2753 | 58.99 | 3068 | 0.3726 | 0.8661 | |
|
| 0.2831 | 59.99 | 3120 | 0.3981 | 0.8635 | |
|
| 0.261 | 60.99 | 3172 | 0.4217 | 0.8635 | |
|
| 0.2662 | 61.99 | 3224 | 0.3516 | 0.8728 | |
|
| 0.2464 | 62.99 | 3276 | 0.3821 | 0.8648 | |
|
| 0.256 | 63.99 | 3328 | 0.3970 | 0.8688 | |
|
| 0.2755 | 64.99 | 3380 | 0.4765 | 0.8541 | |
|
| 0.2339 | 65.99 | 3432 | 0.5616 | 0.8541 | |
|
| 0.2344 | 66.99 | 3484 | 0.3887 | 0.8648 | |
|
| 0.1995 | 67.99 | 3536 | 0.4400 | 0.8675 | |
|
| 0.2297 | 68.99 | 3588 | 0.4290 | 0.8688 | |
|
| 0.227 | 69.99 | 3640 | 0.4521 | 0.8701 | |
|
| 0.2084 | 70.99 | 3692 | 0.3855 | 0.8782 | |
|
| 0.2225 | 71.99 | 3744 | 0.4201 | 0.8742 | |
|
| 0.1897 | 72.99 | 3796 | 0.5138 | 0.8501 | |
|
| 0.2136 | 73.99 | 3848 | 0.4111 | 0.8849 | |
|
| 0.2155 | 74.99 | 3900 | 0.3800 | 0.8862 | |
|
| 0.2338 | 75.99 | 3952 | 0.4014 | 0.8835 | |
|
| 0.2021 | 76.99 | 4004 | 0.4214 | 0.8929 | |
|
| 0.2028 | 77.99 | 4056 | 0.3997 | 0.8795 | |
|
| 0.2162 | 78.99 | 4108 | 0.4911 | 0.8782 | |
|
| 0.1889 | 79.99 | 4160 | 0.4651 | 0.8701 | |
|
| 0.2056 | 80.99 | 4212 | 0.4156 | 0.8862 | |
|
| 0.206 | 81.99 | 4264 | 0.4330 | 0.8742 | |
|
| 0.1919 | 82.99 | 4316 | 0.4199 | 0.8956 | |
|
| 0.1967 | 83.99 | 4368 | 0.4615 | 0.8822 | |
|
| 0.2083 | 84.99 | 4420 | 0.4585 | 0.8715 | |
|
| 0.1888 | 85.99 | 4472 | 0.5748 | 0.8728 | |
|
| 0.1744 | 86.99 | 4524 | 0.4458 | 0.8902 | |
|
| 0.1789 | 87.99 | 4576 | 0.4858 | 0.8688 | |
|
| 0.1992 | 88.99 | 4628 | 0.5018 | 0.8715 | |
|
| 0.1742 | 89.99 | 4680 | 0.5066 | 0.8755 | |
|
| 0.1822 | 90.99 | 4732 | 0.4269 | 0.8929 | |
|
| 0.1883 | 91.99 | 4784 | 0.4550 | 0.8795 | |
|
| 0.1741 | 92.99 | 4836 | 0.4107 | 0.8942 | |
|
| 0.1574 | 93.99 | 4888 | 0.5604 | 0.8809 | |
|
| 0.193 | 94.99 | 4940 | 0.4775 | 0.8889 | |
|
| 0.2018 | 95.99 | 4992 | 0.4200 | 0.8996 | |
|
| 0.1832 | 96.99 | 5044 | 0.4504 | 0.9023 | |
|
| 0.1624 | 97.99 | 5096 | 0.4859 | 0.8889 | |
|
| 0.1739 | 98.99 | 5148 | 0.4955 | 0.8849 | |
|
| 0.1439 | 99.99 | 5200 | 0.4792 | 0.8942 | |
|
| 0.1716 | 100.99 | 5252 | 0.5112 | 0.8862 | |
|
| 0.1537 | 101.99 | 5304 | 0.4572 | 0.8916 | |
|
| 0.1655 | 102.99 | 5356 | 0.4774 | 0.8809 | |
|
| 0.1515 | 103.99 | 5408 | 0.4635 | 0.8889 | |
|
| 0.1594 | 104.99 | 5460 | 0.4794 | 0.8929 | |
|
| 0.1488 | 105.99 | 5512 | 0.4941 | 0.8969 | |
|
| 0.1634 | 106.99 | 5564 | 0.4841 | 0.8916 | |
|
| 0.1471 | 107.99 | 5616 | 0.4919 | 0.9009 | |
|
| 0.1453 | 108.99 | 5668 | 0.4617 | 0.9009 | |
|
| 0.1578 | 109.99 | 5720 | 0.4328 | 0.9009 | |
|
| 0.1754 | 110.99 | 5772 | 0.5240 | 0.8956 | |
|
| 0.1657 | 111.99 | 5824 | 0.4821 | 0.8969 | |
|
| 0.1516 | 112.99 | 5876 | 0.4411 | 0.9023 | |
|
| 0.1542 | 113.99 | 5928 | 0.5313 | 0.8822 | |
|
| 0.1496 | 114.99 | 5980 | 0.5038 | 0.8862 | |
|
| 0.1597 | 115.99 | 6032 | 0.4908 | 0.8876 | |
|
| 0.1175 | 116.99 | 6084 | 0.5504 | 0.8862 | |
|
| 0.1415 | 117.99 | 6136 | 0.5018 | 0.8916 | |
|
| 0.1614 | 118.99 | 6188 | 0.5221 | 0.8902 | |
|
| 0.1396 | 119.99 | 6240 | 0.5042 | 0.8902 | |
|
| 0.1673 | 120.99 | 6292 | 0.5078 | 0.8876 | |
|
| 0.1303 | 121.99 | 6344 | 0.4994 | 0.8942 | |
|
| 0.1355 | 122.99 | 6396 | 0.4834 | 0.8942 | |
|
| 0.1452 | 123.99 | 6448 | 0.5145 | 0.8889 | |
|
| 0.142 | 124.99 | 6500 | 0.5480 | 0.8822 | |
|
| 0.1318 | 125.99 | 6552 | 0.5099 | 0.8916 | |
|
| 0.122 | 126.99 | 6604 | 0.5159 | 0.8876 | |
|
| 0.1678 | 127.99 | 6656 | 0.5080 | 0.8916 | |
|
| 0.1444 | 128.99 | 6708 | 0.5114 | 0.8902 | |
|
| 0.1282 | 129.99 | 6760 | 0.5224 | 0.8889 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.7.0 |
|
- Tokenizers 0.13.2 |
|
|