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README.md
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| 1 |
+
---
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| 2 |
+
license: apache-2.0
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| 3 |
+
base_model: microsoft/swin-tiny-patch4-window7-224
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| 4 |
+
tags:
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| 5 |
+
- generated_from_trainer
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| 6 |
+
datasets:
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| 7 |
+
- imagefolder
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| 8 |
+
metrics:
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| 9 |
+
- accuracy
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| 10 |
+
model-index:
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| 11 |
+
- name: swin-tiny-patch4-window7-224-finetuned-st-ucihar
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| 12 |
+
results:
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| 13 |
+
- task:
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| 14 |
+
name: Image Classification
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| 15 |
+
type: image-classification
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| 16 |
+
dataset:
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| 17 |
+
name: imagefolder
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| 18 |
+
type: imagefolder
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| 19 |
+
config: default
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+
split: train
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| 21 |
+
args: default
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| 22 |
+
metrics:
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| 23 |
+
- name: Accuracy
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| 24 |
+
type: accuracy
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| 25 |
+
value: 0.8363553943789664
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| 26 |
+
---
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| 27 |
+
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| 28 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 29 |
+
should probably proofread and complete it, then remove this comment. -->
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| 30 |
+
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| 31 |
+
# swin-tiny-patch4-window7-224-finetuned-st-ucihar
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| 32 |
+
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| 33 |
+
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.
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| 34 |
+
It achieves the following results on the evaluation set:
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| 35 |
+
- Loss: 0.7803
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| 36 |
+
- Accuracy: 0.8364
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| 37 |
+
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| 38 |
+
## Model description
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| 39 |
+
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| 40 |
+
More information needed
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| 41 |
+
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+
## Intended uses & limitations
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| 43 |
+
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| 44 |
+
More information needed
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| 45 |
+
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| 46 |
+
## Training and evaluation data
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| 47 |
+
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| 48 |
+
More information needed
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| 49 |
+
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| 50 |
+
## Training procedure
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| 51 |
+
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| 52 |
+
### Training hyperparameters
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| 53 |
+
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| 54 |
+
The following hyperparameters were used during training:
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| 55 |
+
- learning_rate: 5e-05
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| 56 |
+
- train_batch_size: 32
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| 57 |
+
- eval_batch_size: 32
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+
- seed: 42
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| 59 |
+
- gradient_accumulation_steps: 4
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| 60 |
+
- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| 62 |
+
- lr_scheduler_type: linear
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| 63 |
+
- lr_scheduler_warmup_ratio: 0.1
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| 64 |
+
- num_epochs: 200
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| 65 |
+
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| 66 |
+
### Training results
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| 67 |
+
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| 68 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 69 |
+
|:-------------:|:--------:|:----:|:---------------:|:--------:|
|
| 70 |
+
| 1.6826 | 0.9938 | 40 | 1.6510 | 0.3504 |
|
| 71 |
+
| 1.3306 | 1.9876 | 80 | 1.2070 | 0.4710 |
|
| 72 |
+
| 1.0249 | 2.9814 | 120 | 0.9149 | 0.5512 |
|
| 73 |
+
| 0.8922 | 4.0 | 161 | 0.7313 | 0.6587 |
|
| 74 |
+
| 0.791 | 4.9938 | 201 | 0.6777 | 0.6881 |
|
| 75 |
+
| 0.7267 | 5.9876 | 241 | 0.6398 | 0.7026 |
|
| 76 |
+
| 0.7106 | 6.9814 | 281 | 0.6299 | 0.7035 |
|
| 77 |
+
| 0.7038 | 8.0 | 322 | 0.6062 | 0.7058 |
|
| 78 |
+
| 0.6694 | 8.9938 | 362 | 0.5736 | 0.7226 |
|
| 79 |
+
| 0.6489 | 9.9876 | 402 | 0.5858 | 0.7248 |
|
| 80 |
+
| 0.6587 | 10.9814 | 442 | 0.5437 | 0.7434 |
|
| 81 |
+
| 0.6376 | 12.0 | 483 | 0.5259 | 0.7520 |
|
| 82 |
+
| 0.6494 | 12.9938 | 523 | 0.5807 | 0.7307 |
|
| 83 |
+
| 0.6236 | 13.9876 | 563 | 0.5236 | 0.7430 |
|
| 84 |
+
| 0.5931 | 14.9814 | 603 | 0.5463 | 0.7384 |
|
| 85 |
+
| 0.605 | 16.0 | 644 | 0.5360 | 0.7371 |
|
| 86 |
+
| 0.5422 | 16.9938 | 684 | 0.4954 | 0.7788 |
|
| 87 |
+
| 0.5485 | 17.9876 | 724 | 0.4910 | 0.7756 |
|
| 88 |
+
| 0.5586 | 18.9814 | 764 | 0.5052 | 0.7738 |
|
| 89 |
+
| 0.6011 | 20.0 | 805 | 0.5036 | 0.7679 |
|
| 90 |
+
| 0.5726 | 20.9938 | 845 | 0.5308 | 0.7588 |
|
| 91 |
+
| 0.514 | 21.9876 | 885 | 0.5064 | 0.7720 |
|
| 92 |
+
| 0.5431 | 22.9814 | 925 | 0.4680 | 0.7892 |
|
| 93 |
+
| 0.5348 | 24.0 | 966 | 0.6083 | 0.7430 |
|
| 94 |
+
| 0.532 | 24.9938 | 1006 | 0.4889 | 0.7815 |
|
| 95 |
+
| 0.5263 | 25.9876 | 1046 | 0.5268 | 0.7634 |
|
| 96 |
+
| 0.497 | 26.9814 | 1086 | 0.5057 | 0.7779 |
|
| 97 |
+
| 0.4929 | 28.0 | 1127 | 0.5560 | 0.7570 |
|
| 98 |
+
| 0.4828 | 28.9938 | 1167 | 0.4701 | 0.7928 |
|
| 99 |
+
| 0.4604 | 29.9876 | 1207 | 0.4656 | 0.8001 |
|
| 100 |
+
| 0.4472 | 30.9814 | 1247 | 0.4619 | 0.8083 |
|
| 101 |
+
| 0.455 | 32.0 | 1288 | 0.4920 | 0.7969 |
|
| 102 |
+
| 0.4467 | 32.9938 | 1328 | 0.4698 | 0.7987 |
|
| 103 |
+
| 0.4327 | 33.9876 | 1368 | 0.4489 | 0.8055 |
|
| 104 |
+
| 0.3918 | 34.9814 | 1408 | 0.5249 | 0.7906 |
|
| 105 |
+
| 0.4222 | 36.0 | 1449 | 0.4380 | 0.8069 |
|
| 106 |
+
| 0.3864 | 36.9938 | 1489 | 0.4695 | 0.8128 |
|
| 107 |
+
| 0.3865 | 37.9876 | 1529 | 0.5208 | 0.7811 |
|
| 108 |
+
| 0.3759 | 38.9814 | 1569 | 0.4972 | 0.8019 |
|
| 109 |
+
| 0.375 | 40.0 | 1610 | 0.4667 | 0.8105 |
|
| 110 |
+
| 0.4016 | 40.9938 | 1650 | 0.4632 | 0.8178 |
|
| 111 |
+
| 0.3788 | 41.9876 | 1690 | 0.4670 | 0.8078 |
|
| 112 |
+
| 0.3517 | 42.9814 | 1730 | 0.4745 | 0.8101 |
|
| 113 |
+
| 0.3707 | 44.0 | 1771 | 0.4526 | 0.8187 |
|
| 114 |
+
| 0.3422 | 44.9938 | 1811 | 0.4893 | 0.8005 |
|
| 115 |
+
| 0.3661 | 45.9876 | 1851 | 0.4748 | 0.8087 |
|
| 116 |
+
| 0.3522 | 46.9814 | 1891 | 0.4923 | 0.7992 |
|
| 117 |
+
| 0.385 | 48.0 | 1932 | 0.4335 | 0.8273 |
|
| 118 |
+
| 0.306 | 48.9938 | 1972 | 0.4823 | 0.8228 |
|
| 119 |
+
| 0.3163 | 49.9876 | 2012 | 0.5157 | 0.8069 |
|
| 120 |
+
| 0.3199 | 50.9814 | 2052 | 0.5283 | 0.8015 |
|
| 121 |
+
| 0.3248 | 52.0 | 2093 | 0.4652 | 0.8191 |
|
| 122 |
+
| 0.2969 | 52.9938 | 2133 | 0.5260 | 0.8024 |
|
| 123 |
+
| 0.3138 | 53.9876 | 2173 | 0.4862 | 0.8069 |
|
| 124 |
+
| 0.2665 | 54.9814 | 2213 | 0.4781 | 0.8250 |
|
| 125 |
+
| 0.2932 | 56.0 | 2254 | 0.5094 | 0.8214 |
|
| 126 |
+
| 0.2819 | 56.9938 | 2294 | 0.4921 | 0.8178 |
|
| 127 |
+
| 0.2677 | 57.9876 | 2334 | 0.5372 | 0.8087 |
|
| 128 |
+
| 0.2623 | 58.9814 | 2374 | 0.4847 | 0.8286 |
|
| 129 |
+
| 0.2584 | 60.0 | 2415 | 0.5754 | 0.8069 |
|
| 130 |
+
| 0.2637 | 60.9938 | 2455 | 0.5297 | 0.8182 |
|
| 131 |
+
| 0.2391 | 61.9876 | 2495 | 0.5187 | 0.8214 |
|
| 132 |
+
| 0.2426 | 62.9814 | 2535 | 0.5719 | 0.8137 |
|
| 133 |
+
| 0.2405 | 64.0 | 2576 | 0.5118 | 0.8232 |
|
| 134 |
+
| 0.2132 | 64.9938 | 2616 | 0.5691 | 0.8123 |
|
| 135 |
+
| 0.2572 | 65.9876 | 2656 | 0.5452 | 0.8209 |
|
| 136 |
+
| 0.2255 | 66.9814 | 2696 | 0.5650 | 0.8073 |
|
| 137 |
+
| 0.2614 | 68.0 | 2737 | 0.5387 | 0.8214 |
|
| 138 |
+
| 0.2284 | 68.9938 | 2777 | 0.6056 | 0.8141 |
|
| 139 |
+
| 0.2371 | 69.9876 | 2817 | 0.5906 | 0.8128 |
|
| 140 |
+
| 0.2089 | 70.9814 | 2857 | 0.5550 | 0.8119 |
|
| 141 |
+
| 0.2276 | 72.0 | 2898 | 0.5511 | 0.8214 |
|
| 142 |
+
| 0.2192 | 72.9938 | 2938 | 0.6162 | 0.8259 |
|
| 143 |
+
| 0.2076 | 73.9876 | 2978 | 0.5663 | 0.8237 |
|
| 144 |
+
| 0.1938 | 74.9814 | 3018 | 0.6118 | 0.8191 |
|
| 145 |
+
| 0.2274 | 76.0 | 3059 | 0.5603 | 0.8268 |
|
| 146 |
+
| 0.2271 | 76.9938 | 3099 | 0.6312 | 0.8128 |
|
| 147 |
+
| 0.2023 | 77.9876 | 3139 | 0.6300 | 0.8123 |
|
| 148 |
+
| 0.1792 | 78.9814 | 3179 | 0.5776 | 0.8268 |
|
| 149 |
+
| 0.1796 | 80.0 | 3220 | 0.6266 | 0.8209 |
|
| 150 |
+
| 0.1994 | 80.9938 | 3260 | 0.5468 | 0.8228 |
|
| 151 |
+
| 0.1857 | 81.9876 | 3300 | 0.6080 | 0.8205 |
|
| 152 |
+
| 0.1636 | 82.9814 | 3340 | 0.7066 | 0.8160 |
|
| 153 |
+
| 0.1665 | 84.0 | 3381 | 0.6064 | 0.8277 |
|
| 154 |
+
| 0.183 | 84.9938 | 3421 | 0.6019 | 0.8273 |
|
| 155 |
+
| 0.1761 | 85.9876 | 3461 | 0.6420 | 0.8196 |
|
| 156 |
+
| 0.1673 | 86.9814 | 3501 | 0.6287 | 0.8255 |
|
| 157 |
+
| 0.1946 | 88.0 | 3542 | 0.6024 | 0.8228 |
|
| 158 |
+
| 0.1511 | 88.9938 | 3582 | 0.6774 | 0.8169 |
|
| 159 |
+
| 0.1828 | 89.9876 | 3622 | 0.6015 | 0.8255 |
|
| 160 |
+
| 0.1758 | 90.9814 | 3662 | 0.5969 | 0.8300 |
|
| 161 |
+
| 0.1797 | 92.0 | 3703 | 0.6464 | 0.8200 |
|
| 162 |
+
| 0.176 | 92.9938 | 3743 | 0.6287 | 0.8173 |
|
| 163 |
+
| 0.1616 | 93.9876 | 3783 | 0.6914 | 0.8209 |
|
| 164 |
+
| 0.1783 | 94.9814 | 3823 | 0.6511 | 0.8218 |
|
| 165 |
+
| 0.1492 | 96.0 | 3864 | 0.6382 | 0.8264 |
|
| 166 |
+
| 0.1578 | 96.9938 | 3904 | 0.6391 | 0.8241 |
|
| 167 |
+
| 0.1574 | 97.9876 | 3944 | 0.6505 | 0.8255 |
|
| 168 |
+
| 0.1556 | 98.9814 | 3984 | 0.6302 | 0.8241 |
|
| 169 |
+
| 0.1396 | 100.0 | 4025 | 0.6634 | 0.8155 |
|
| 170 |
+
| 0.1246 | 100.9938 | 4065 | 0.6633 | 0.8264 |
|
| 171 |
+
| 0.1592 | 101.9876 | 4105 | 0.6815 | 0.8160 |
|
| 172 |
+
| 0.1393 | 102.9814 | 4145 | 0.6418 | 0.8237 |
|
| 173 |
+
| 0.1722 | 104.0 | 4186 | 0.6322 | 0.8318 |
|
| 174 |
+
| 0.1499 | 104.9938 | 4226 | 0.6901 | 0.8196 |
|
| 175 |
+
| 0.1282 | 105.9876 | 4266 | 0.6544 | 0.8309 |
|
| 176 |
+
| 0.1428 | 106.9814 | 4306 | 0.6581 | 0.8291 |
|
| 177 |
+
| 0.1478 | 108.0 | 4347 | 0.6825 | 0.8291 |
|
| 178 |
+
| 0.1453 | 108.9938 | 4387 | 0.6873 | 0.8237 |
|
| 179 |
+
| 0.1216 | 109.9876 | 4427 | 0.7075 | 0.8223 |
|
| 180 |
+
| 0.1449 | 110.9814 | 4467 | 0.6929 | 0.8232 |
|
| 181 |
+
| 0.137 | 112.0 | 4508 | 0.7139 | 0.8205 |
|
| 182 |
+
| 0.1177 | 112.9938 | 4548 | 0.6981 | 0.8305 |
|
| 183 |
+
| 0.1005 | 113.9876 | 4588 | 0.6840 | 0.8205 |
|
| 184 |
+
| 0.1305 | 114.9814 | 4628 | 0.6747 | 0.8273 |
|
| 185 |
+
| 0.1192 | 116.0 | 4669 | 0.6886 | 0.8259 |
|
| 186 |
+
| 0.1067 | 116.9938 | 4709 | 0.6612 | 0.8209 |
|
| 187 |
+
| 0.1122 | 117.9876 | 4749 | 0.6500 | 0.8259 |
|
| 188 |
+
| 0.1295 | 118.9814 | 4789 | 0.6948 | 0.8232 |
|
| 189 |
+
| 0.1304 | 120.0 | 4830 | 0.6651 | 0.8309 |
|
| 190 |
+
| 0.1334 | 120.9938 | 4870 | 0.7304 | 0.8187 |
|
| 191 |
+
| 0.1104 | 121.9876 | 4910 | 0.7365 | 0.8205 |
|
| 192 |
+
| 0.1132 | 122.9814 | 4950 | 0.7270 | 0.8300 |
|
| 193 |
+
| 0.1115 | 124.0 | 4991 | 0.7062 | 0.8228 |
|
| 194 |
+
| 0.1079 | 124.9938 | 5031 | 0.7579 | 0.8268 |
|
| 195 |
+
| 0.1192 | 125.9876 | 5071 | 0.7321 | 0.8205 |
|
| 196 |
+
| 0.0994 | 126.9814 | 5111 | 0.7219 | 0.8291 |
|
| 197 |
+
| 0.111 | 128.0 | 5152 | 0.7064 | 0.8273 |
|
| 198 |
+
| 0.1089 | 128.9938 | 5192 | 0.7056 | 0.8282 |
|
| 199 |
+
| 0.1062 | 129.9876 | 5232 | 0.6814 | 0.8323 |
|
| 200 |
+
| 0.1046 | 130.9814 | 5272 | 0.6843 | 0.8309 |
|
| 201 |
+
| 0.1013 | 132.0 | 5313 | 0.6807 | 0.8327 |
|
| 202 |
+
| 0.0879 | 132.9938 | 5353 | 0.7080 | 0.8336 |
|
| 203 |
+
| 0.1114 | 133.9876 | 5393 | 0.7129 | 0.8241 |
|
| 204 |
+
| 0.1133 | 134.9814 | 5433 | 0.7376 | 0.8264 |
|
| 205 |
+
| 0.1067 | 136.0 | 5474 | 0.7579 | 0.8259 |
|
| 206 |
+
| 0.1104 | 136.9938 | 5514 | 0.7178 | 0.8291 |
|
| 207 |
+
| 0.0893 | 137.9876 | 5554 | 0.7315 | 0.8300 |
|
| 208 |
+
| 0.1074 | 138.9814 | 5594 | 0.7312 | 0.8318 |
|
| 209 |
+
| 0.0983 | 140.0 | 5635 | 0.7362 | 0.8286 |
|
| 210 |
+
| 0.1093 | 140.9938 | 5675 | 0.7493 | 0.8286 |
|
| 211 |
+
| 0.1166 | 141.9876 | 5715 | 0.7205 | 0.8286 |
|
| 212 |
+
| 0.0969 | 142.9814 | 5755 | 0.7494 | 0.8291 |
|
| 213 |
+
| 0.1174 | 144.0 | 5796 | 0.6960 | 0.8336 |
|
| 214 |
+
| 0.1044 | 144.9938 | 5836 | 0.7111 | 0.8282 |
|
| 215 |
+
| 0.0866 | 145.9876 | 5876 | 0.7152 | 0.8364 |
|
| 216 |
+
| 0.092 | 146.9814 | 5916 | 0.7078 | 0.8327 |
|
| 217 |
+
| 0.0883 | 148.0 | 5957 | 0.7182 | 0.8341 |
|
| 218 |
+
| 0.0824 | 148.9938 | 5997 | 0.7095 | 0.8359 |
|
| 219 |
+
| 0.0953 | 149.9876 | 6037 | 0.7324 | 0.8354 |
|
| 220 |
+
| 0.0896 | 150.9814 | 6077 | 0.7032 | 0.8400 |
|
| 221 |
+
| 0.1025 | 152.0 | 6118 | 0.6938 | 0.8323 |
|
| 222 |
+
| 0.0966 | 152.9938 | 6158 | 0.6991 | 0.8404 |
|
| 223 |
+
| 0.0891 | 153.9876 | 6198 | 0.7346 | 0.8354 |
|
| 224 |
+
| 0.0733 | 154.9814 | 6238 | 0.7340 | 0.8350 |
|
| 225 |
+
| 0.0944 | 156.0 | 6279 | 0.7525 | 0.8277 |
|
| 226 |
+
| 0.0934 | 156.9938 | 6319 | 0.7683 | 0.8305 |
|
| 227 |
+
| 0.0768 | 157.9876 | 6359 | 0.7692 | 0.8286 |
|
| 228 |
+
| 0.0918 | 158.9814 | 6399 | 0.7387 | 0.8413 |
|
| 229 |
+
| 0.0886 | 160.0 | 6440 | 0.7705 | 0.8327 |
|
| 230 |
+
| 0.0836 | 160.9938 | 6480 | 0.7491 | 0.8327 |
|
| 231 |
+
| 0.0968 | 161.9876 | 6520 | 0.7663 | 0.8246 |
|
| 232 |
+
| 0.0748 | 162.9814 | 6560 | 0.7460 | 0.8305 |
|
| 233 |
+
| 0.0696 | 164.0 | 6601 | 0.7491 | 0.8332 |
|
| 234 |
+
| 0.0853 | 164.9938 | 6641 | 0.7788 | 0.8327 |
|
| 235 |
+
| 0.0726 | 165.9876 | 6681 | 0.7440 | 0.8382 |
|
| 236 |
+
| 0.0715 | 166.9814 | 6721 | 0.7518 | 0.8373 |
|
| 237 |
+
| 0.0699 | 168.0 | 6762 | 0.7574 | 0.8354 |
|
| 238 |
+
| 0.0749 | 168.9938 | 6802 | 0.7564 | 0.8323 |
|
| 239 |
+
| 0.0842 | 169.9876 | 6842 | 0.7829 | 0.8286 |
|
| 240 |
+
| 0.0822 | 170.9814 | 6882 | 0.7753 | 0.8327 |
|
| 241 |
+
| 0.0807 | 172.0 | 6923 | 0.7611 | 0.8359 |
|
| 242 |
+
| 0.0752 | 172.9938 | 6963 | 0.7673 | 0.8345 |
|
| 243 |
+
| 0.075 | 173.9876 | 7003 | 0.7815 | 0.8364 |
|
| 244 |
+
| 0.0845 | 174.9814 | 7043 | 0.7745 | 0.8382 |
|
| 245 |
+
| 0.0827 | 176.0 | 7084 | 0.7683 | 0.8373 |
|
| 246 |
+
| 0.0883 | 176.9938 | 7124 | 0.7842 | 0.8327 |
|
| 247 |
+
| 0.0774 | 177.9876 | 7164 | 0.7736 | 0.8368 |
|
| 248 |
+
| 0.0817 | 178.9814 | 7204 | 0.7852 | 0.8341 |
|
| 249 |
+
| 0.0804 | 180.0 | 7245 | 0.7686 | 0.8314 |
|
| 250 |
+
| 0.0671 | 180.9938 | 7285 | 0.7767 | 0.8359 |
|
| 251 |
+
| 0.076 | 181.9876 | 7325 | 0.7715 | 0.8350 |
|
| 252 |
+
| 0.0572 | 182.9814 | 7365 | 0.7740 | 0.8286 |
|
| 253 |
+
| 0.0823 | 184.0 | 7406 | 0.7757 | 0.8341 |
|
| 254 |
+
| 0.0662 | 184.9938 | 7446 | 0.7720 | 0.8336 |
|
| 255 |
+
| 0.0805 | 185.9876 | 7486 | 0.7696 | 0.8368 |
|
| 256 |
+
| 0.0763 | 186.9814 | 7526 | 0.7768 | 0.8377 |
|
| 257 |
+
| 0.0711 | 188.0 | 7567 | 0.7720 | 0.8350 |
|
| 258 |
+
| 0.0576 | 188.9938 | 7607 | 0.7845 | 0.8314 |
|
| 259 |
+
| 0.0667 | 189.9876 | 7647 | 0.7749 | 0.8336 |
|
| 260 |
+
| 0.0631 | 190.9814 | 7687 | 0.7774 | 0.8350 |
|
| 261 |
+
| 0.0744 | 192.0 | 7728 | 0.7778 | 0.8327 |
|
| 262 |
+
| 0.0672 | 192.9938 | 7768 | 0.7862 | 0.8323 |
|
| 263 |
+
| 0.0738 | 193.9876 | 7808 | 0.7843 | 0.8345 |
|
| 264 |
+
| 0.0754 | 194.9814 | 7848 | 0.7850 | 0.8368 |
|
| 265 |
+
| 0.0887 | 196.0 | 7889 | 0.7835 | 0.8364 |
|
| 266 |
+
| 0.0898 | 196.9938 | 7929 | 0.7810 | 0.8373 |
|
| 267 |
+
| 0.0543 | 197.9876 | 7969 | 0.7801 | 0.8364 |
|
| 268 |
+
| 0.0605 | 198.7578 | 8000 | 0.7803 | 0.8364 |
|
| 269 |
+
|
| 270 |
+
|
| 271 |
+
### Framework versions
|
| 272 |
+
|
| 273 |
+
- Transformers 4.44.0
|
| 274 |
+
- Pytorch 1.12.1+cu113
|
| 275 |
+
- Datasets 2.21.0
|
| 276 |
+
- Tokenizers 0.19.1
|
model.safetensors
CHANGED
|
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| 1 |
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| 2 |
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size 110355136
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| 1 |
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| 3 |
size 110355136
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runs/Aug28_17-53-01_jrcai27/events.out.tfevents.1724856787.jrcai27.14540.0
CHANGED
|
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|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 2 |
-
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| 3 |
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size
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|
| 1 |
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size 238885
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