Commit
·
aa6f76d
1
Parent(s):
f851dcc
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,206 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- imagefolder
|
| 7 |
+
metrics:
|
| 8 |
+
- accuracy
|
| 9 |
+
model-index:
|
| 10 |
+
- name: swin-tiny-patch4-window7-224-finetuned-woody_LeftGR_clean_130epochs
|
| 11 |
+
results:
|
| 12 |
+
- task:
|
| 13 |
+
name: Image Classification
|
| 14 |
+
type: image-classification
|
| 15 |
+
dataset:
|
| 16 |
+
name: imagefolder
|
| 17 |
+
type: imagefolder
|
| 18 |
+
config: default
|
| 19 |
+
split: train
|
| 20 |
+
args: default
|
| 21 |
+
metrics:
|
| 22 |
+
- name: Accuracy
|
| 23 |
+
type: accuracy
|
| 24 |
+
value: 0.8888888888888888
|
| 25 |
+
---
|
| 26 |
+
|
| 27 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 28 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 29 |
+
|
| 30 |
+
# swin-tiny-patch4-window7-224-finetuned-woody_LeftGR_clean_130epochs
|
| 31 |
+
|
| 32 |
+
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.
|
| 33 |
+
It achieves the following results on the evaluation set:
|
| 34 |
+
- Loss: 0.5224
|
| 35 |
+
- Accuracy: 0.8889
|
| 36 |
+
|
| 37 |
+
## Model description
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Intended uses & limitations
|
| 42 |
+
|
| 43 |
+
More information needed
|
| 44 |
+
|
| 45 |
+
## Training and evaluation data
|
| 46 |
+
|
| 47 |
+
More information needed
|
| 48 |
+
|
| 49 |
+
## Training procedure
|
| 50 |
+
|
| 51 |
+
### Training hyperparameters
|
| 52 |
+
|
| 53 |
+
The following hyperparameters were used during training:
|
| 54 |
+
- learning_rate: 5e-05
|
| 55 |
+
- train_batch_size: 32
|
| 56 |
+
- eval_batch_size: 32
|
| 57 |
+
- seed: 42
|
| 58 |
+
- gradient_accumulation_steps: 4
|
| 59 |
+
- total_train_batch_size: 128
|
| 60 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 61 |
+
- lr_scheduler_type: linear
|
| 62 |
+
- lr_scheduler_warmup_ratio: 0.1
|
| 63 |
+
- num_epochs: 130
|
| 64 |
+
|
| 65 |
+
### Training results
|
| 66 |
+
|
| 67 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
| 68 |
+
|:-------------:|:------:|:----:|:---------------:|:--------:|
|
| 69 |
+
| 0.6569 | 0.99 | 52 | 0.6227 | 0.6720 |
|
| 70 |
+
| 0.6069 | 1.99 | 104 | 0.5891 | 0.6934 |
|
| 71 |
+
| 0.6044 | 2.99 | 156 | 0.5543 | 0.7202 |
|
| 72 |
+
| 0.5898 | 3.99 | 208 | 0.5440 | 0.7229 |
|
| 73 |
+
| 0.5774 | 4.99 | 260 | 0.5360 | 0.7282 |
|
| 74 |
+
| 0.5912 | 5.99 | 312 | 0.5466 | 0.7189 |
|
| 75 |
+
| 0.5685 | 6.99 | 364 | 0.5184 | 0.7336 |
|
| 76 |
+
| 0.5604 | 7.99 | 416 | 0.5138 | 0.7550 |
|
| 77 |
+
| 0.5455 | 8.99 | 468 | 0.5157 | 0.7376 |
|
| 78 |
+
| 0.5462 | 9.99 | 520 | 0.5078 | 0.7657 |
|
| 79 |
+
| 0.5729 | 10.99 | 572 | 0.4957 | 0.7523 |
|
| 80 |
+
| 0.5555 | 11.99 | 624 | 0.5016 | 0.7564 |
|
| 81 |
+
| 0.5291 | 12.99 | 676 | 0.5665 | 0.7323 |
|
| 82 |
+
| 0.524 | 13.99 | 728 | 0.5431 | 0.7390 |
|
| 83 |
+
| 0.5194 | 14.99 | 780 | 0.5019 | 0.7430 |
|
| 84 |
+
| 0.5368 | 15.99 | 832 | 0.4810 | 0.7724 |
|
| 85 |
+
| 0.4917 | 16.99 | 884 | 0.4793 | 0.7711 |
|
| 86 |
+
| 0.4892 | 17.99 | 936 | 0.4981 | 0.7631 |
|
| 87 |
+
| 0.5117 | 18.99 | 988 | 0.4969 | 0.7510 |
|
| 88 |
+
| 0.5033 | 19.99 | 1040 | 0.4711 | 0.7671 |
|
| 89 |
+
| 0.4807 | 20.99 | 1092 | 0.4959 | 0.7724 |
|
| 90 |
+
| 0.493 | 21.99 | 1144 | 0.4509 | 0.7898 |
|
| 91 |
+
| 0.4887 | 22.99 | 1196 | 0.4791 | 0.7738 |
|
| 92 |
+
| 0.4517 | 23.99 | 1248 | 0.4722 | 0.7831 |
|
| 93 |
+
| 0.4617 | 24.99 | 1300 | 0.4344 | 0.7992 |
|
| 94 |
+
| 0.4609 | 25.99 | 1352 | 0.4647 | 0.7952 |
|
| 95 |
+
| 0.4365 | 26.99 | 1404 | 0.4459 | 0.7912 |
|
| 96 |
+
| 0.4515 | 27.99 | 1456 | 0.5217 | 0.7644 |
|
| 97 |
+
| 0.4538 | 28.99 | 1508 | 0.4375 | 0.8166 |
|
| 98 |
+
| 0.4371 | 29.99 | 1560 | 0.4406 | 0.8005 |
|
| 99 |
+
| 0.4228 | 30.99 | 1612 | 0.4383 | 0.7912 |
|
| 100 |
+
| 0.4347 | 31.99 | 1664 | 0.4246 | 0.8153 |
|
| 101 |
+
| 0.4354 | 32.99 | 1716 | 0.4606 | 0.8112 |
|
| 102 |
+
| 0.4194 | 33.99 | 1768 | 0.4371 | 0.8112 |
|
| 103 |
+
| 0.4073 | 34.99 | 1820 | 0.4436 | 0.8126 |
|
| 104 |
+
| 0.3935 | 35.99 | 1872 | 0.4255 | 0.8273 |
|
| 105 |
+
| 0.3862 | 36.99 | 1924 | 0.4054 | 0.8233 |
|
| 106 |
+
| 0.3739 | 37.99 | 1976 | 0.4206 | 0.8126 |
|
| 107 |
+
| 0.3794 | 38.99 | 2028 | 0.4075 | 0.8220 |
|
| 108 |
+
| 0.3713 | 39.99 | 2080 | 0.3787 | 0.8353 |
|
| 109 |
+
| 0.3901 | 40.99 | 2132 | 0.3840 | 0.8246 |
|
| 110 |
+
| 0.3514 | 41.99 | 2184 | 0.4136 | 0.8367 |
|
| 111 |
+
| 0.3718 | 42.99 | 2236 | 0.3867 | 0.8394 |
|
| 112 |
+
| 0.3699 | 43.99 | 2288 | 0.3737 | 0.8487 |
|
| 113 |
+
| 0.3314 | 44.99 | 2340 | 0.3756 | 0.8527 |
|
| 114 |
+
| 0.3167 | 45.99 | 2392 | 0.4211 | 0.8474 |
|
| 115 |
+
| 0.301 | 46.99 | 2444 | 0.3870 | 0.8434 |
|
| 116 |
+
| 0.3048 | 47.99 | 2496 | 0.4236 | 0.8461 |
|
| 117 |
+
| 0.2735 | 48.99 | 2548 | 0.4122 | 0.8380 |
|
| 118 |
+
| 0.3003 | 49.99 | 2600 | 0.3609 | 0.8568 |
|
| 119 |
+
| 0.3147 | 50.99 | 2652 | 0.4258 | 0.8367 |
|
| 120 |
+
| 0.288 | 51.99 | 2704 | 0.3855 | 0.8394 |
|
| 121 |
+
| 0.2895 | 52.99 | 2756 | 0.3543 | 0.8527 |
|
| 122 |
+
| 0.2685 | 53.99 | 2808 | 0.3668 | 0.8541 |
|
| 123 |
+
| 0.2931 | 54.99 | 2860 | 0.3565 | 0.8541 |
|
| 124 |
+
| 0.2966 | 55.99 | 2912 | 0.3985 | 0.8568 |
|
| 125 |
+
| 0.2737 | 56.99 | 2964 | 0.4100 | 0.8581 |
|
| 126 |
+
| 0.2892 | 57.99 | 3016 | 0.3480 | 0.8768 |
|
| 127 |
+
| 0.2753 | 58.99 | 3068 | 0.3726 | 0.8661 |
|
| 128 |
+
| 0.2831 | 59.99 | 3120 | 0.3981 | 0.8635 |
|
| 129 |
+
| 0.261 | 60.99 | 3172 | 0.4217 | 0.8635 |
|
| 130 |
+
| 0.2662 | 61.99 | 3224 | 0.3516 | 0.8728 |
|
| 131 |
+
| 0.2464 | 62.99 | 3276 | 0.3821 | 0.8648 |
|
| 132 |
+
| 0.256 | 63.99 | 3328 | 0.3970 | 0.8688 |
|
| 133 |
+
| 0.2755 | 64.99 | 3380 | 0.4765 | 0.8541 |
|
| 134 |
+
| 0.2339 | 65.99 | 3432 | 0.5616 | 0.8541 |
|
| 135 |
+
| 0.2344 | 66.99 | 3484 | 0.3887 | 0.8648 |
|
| 136 |
+
| 0.1995 | 67.99 | 3536 | 0.4400 | 0.8675 |
|
| 137 |
+
| 0.2297 | 68.99 | 3588 | 0.4290 | 0.8688 |
|
| 138 |
+
| 0.227 | 69.99 | 3640 | 0.4521 | 0.8701 |
|
| 139 |
+
| 0.2084 | 70.99 | 3692 | 0.3855 | 0.8782 |
|
| 140 |
+
| 0.2225 | 71.99 | 3744 | 0.4201 | 0.8742 |
|
| 141 |
+
| 0.1897 | 72.99 | 3796 | 0.5138 | 0.8501 |
|
| 142 |
+
| 0.2136 | 73.99 | 3848 | 0.4111 | 0.8849 |
|
| 143 |
+
| 0.2155 | 74.99 | 3900 | 0.3800 | 0.8862 |
|
| 144 |
+
| 0.2338 | 75.99 | 3952 | 0.4014 | 0.8835 |
|
| 145 |
+
| 0.2021 | 76.99 | 4004 | 0.4214 | 0.8929 |
|
| 146 |
+
| 0.2028 | 77.99 | 4056 | 0.3997 | 0.8795 |
|
| 147 |
+
| 0.2162 | 78.99 | 4108 | 0.4911 | 0.8782 |
|
| 148 |
+
| 0.1889 | 79.99 | 4160 | 0.4651 | 0.8701 |
|
| 149 |
+
| 0.2056 | 80.99 | 4212 | 0.4156 | 0.8862 |
|
| 150 |
+
| 0.206 | 81.99 | 4264 | 0.4330 | 0.8742 |
|
| 151 |
+
| 0.1919 | 82.99 | 4316 | 0.4199 | 0.8956 |
|
| 152 |
+
| 0.1967 | 83.99 | 4368 | 0.4615 | 0.8822 |
|
| 153 |
+
| 0.2083 | 84.99 | 4420 | 0.4585 | 0.8715 |
|
| 154 |
+
| 0.1888 | 85.99 | 4472 | 0.5748 | 0.8728 |
|
| 155 |
+
| 0.1744 | 86.99 | 4524 | 0.4458 | 0.8902 |
|
| 156 |
+
| 0.1789 | 87.99 | 4576 | 0.4858 | 0.8688 |
|
| 157 |
+
| 0.1992 | 88.99 | 4628 | 0.5018 | 0.8715 |
|
| 158 |
+
| 0.1742 | 89.99 | 4680 | 0.5066 | 0.8755 |
|
| 159 |
+
| 0.1822 | 90.99 | 4732 | 0.4269 | 0.8929 |
|
| 160 |
+
| 0.1883 | 91.99 | 4784 | 0.4550 | 0.8795 |
|
| 161 |
+
| 0.1741 | 92.99 | 4836 | 0.4107 | 0.8942 |
|
| 162 |
+
| 0.1574 | 93.99 | 4888 | 0.5604 | 0.8809 |
|
| 163 |
+
| 0.193 | 94.99 | 4940 | 0.4775 | 0.8889 |
|
| 164 |
+
| 0.2018 | 95.99 | 4992 | 0.4200 | 0.8996 |
|
| 165 |
+
| 0.1832 | 96.99 | 5044 | 0.4504 | 0.9023 |
|
| 166 |
+
| 0.1624 | 97.99 | 5096 | 0.4859 | 0.8889 |
|
| 167 |
+
| 0.1739 | 98.99 | 5148 | 0.4955 | 0.8849 |
|
| 168 |
+
| 0.1439 | 99.99 | 5200 | 0.4792 | 0.8942 |
|
| 169 |
+
| 0.1716 | 100.99 | 5252 | 0.5112 | 0.8862 |
|
| 170 |
+
| 0.1537 | 101.99 | 5304 | 0.4572 | 0.8916 |
|
| 171 |
+
| 0.1655 | 102.99 | 5356 | 0.4774 | 0.8809 |
|
| 172 |
+
| 0.1515 | 103.99 | 5408 | 0.4635 | 0.8889 |
|
| 173 |
+
| 0.1594 | 104.99 | 5460 | 0.4794 | 0.8929 |
|
| 174 |
+
| 0.1488 | 105.99 | 5512 | 0.4941 | 0.8969 |
|
| 175 |
+
| 0.1634 | 106.99 | 5564 | 0.4841 | 0.8916 |
|
| 176 |
+
| 0.1471 | 107.99 | 5616 | 0.4919 | 0.9009 |
|
| 177 |
+
| 0.1453 | 108.99 | 5668 | 0.4617 | 0.9009 |
|
| 178 |
+
| 0.1578 | 109.99 | 5720 | 0.4328 | 0.9009 |
|
| 179 |
+
| 0.1754 | 110.99 | 5772 | 0.5240 | 0.8956 |
|
| 180 |
+
| 0.1657 | 111.99 | 5824 | 0.4821 | 0.8969 |
|
| 181 |
+
| 0.1516 | 112.99 | 5876 | 0.4411 | 0.9023 |
|
| 182 |
+
| 0.1542 | 113.99 | 5928 | 0.5313 | 0.8822 |
|
| 183 |
+
| 0.1496 | 114.99 | 5980 | 0.5038 | 0.8862 |
|
| 184 |
+
| 0.1597 | 115.99 | 6032 | 0.4908 | 0.8876 |
|
| 185 |
+
| 0.1175 | 116.99 | 6084 | 0.5504 | 0.8862 |
|
| 186 |
+
| 0.1415 | 117.99 | 6136 | 0.5018 | 0.8916 |
|
| 187 |
+
| 0.1614 | 118.99 | 6188 | 0.5221 | 0.8902 |
|
| 188 |
+
| 0.1396 | 119.99 | 6240 | 0.5042 | 0.8902 |
|
| 189 |
+
| 0.1673 | 120.99 | 6292 | 0.5078 | 0.8876 |
|
| 190 |
+
| 0.1303 | 121.99 | 6344 | 0.4994 | 0.8942 |
|
| 191 |
+
| 0.1355 | 122.99 | 6396 | 0.4834 | 0.8942 |
|
| 192 |
+
| 0.1452 | 123.99 | 6448 | 0.5145 | 0.8889 |
|
| 193 |
+
| 0.142 | 124.99 | 6500 | 0.5480 | 0.8822 |
|
| 194 |
+
| 0.1318 | 125.99 | 6552 | 0.5099 | 0.8916 |
|
| 195 |
+
| 0.122 | 126.99 | 6604 | 0.5159 | 0.8876 |
|
| 196 |
+
| 0.1678 | 127.99 | 6656 | 0.5080 | 0.8916 |
|
| 197 |
+
| 0.1444 | 128.99 | 6708 | 0.5114 | 0.8902 |
|
| 198 |
+
| 0.1282 | 129.99 | 6760 | 0.5224 | 0.8889 |
|
| 199 |
+
|
| 200 |
+
|
| 201 |
+
### Framework versions
|
| 202 |
+
|
| 203 |
+
- Transformers 4.24.0
|
| 204 |
+
- Pytorch 1.12.1+cu113
|
| 205 |
+
- Datasets 2.7.0
|
| 206 |
+
- Tokenizers 0.13.2
|