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EN
Videomae Base Finetuned Signlanguage Last 3
A video understanding model fine-tuned based on MCG-NJU/videomae-base, specialized in sign language recognition tasks
Downloads 21
Release Time : 3/4/2025
Model Overview
This model is a fine-tuned version based on the VideoMAE architecture, specifically designed for sign language recognition tasks. It achieved an accuracy of 72.81% on the evaluation set.
Model Features
Video Understanding Capability
Based on the VideoMAE architecture, excels at extracting spatiotemporal features from video sequences
Sign Language Recognition Optimization
Fine-tuned specifically for sign language recognition tasks, achieving 72.81% accuracy on the evaluation set
Efficient Training
Utilizes linear learning rate scheduling and warm-up strategies to optimize the training process
Model Capabilities
Video Classification
Sign Language Recognition
Spatiotemporal Feature Extraction
Use Cases
Accessibility Technology
Sign Language Translation System
Real-time conversion of sign language videos into text or speech
Achieved 72.81% recognition accuracy on the evaluation set
Educational Technology
Sign Language Learning Assistance
Evaluating the accuracy of learners' sign language gestures
## 🚀 videomae-base-finetuned-signlanguage-last-3
This model is a fine - tuned version of [MCG - NJU/videomae - base](https://huggingface.co/MCG - NJU/videomae - base) on an unknown dataset. It provides valuable capabilities for sign language recognition tasks, achieving relatively high accuracy on the evaluation set.
## 🚀 Quick Start
This section provides a brief introduction to the model. For more detailed usage, please refer to the official documentation of the `transformers` library.
## 📚 Documentation
### Model description
This model is a fine - tuned version of [MCG - NJU/videomae - base](https://huggingface.co/MCG - NJU/videomae - base) on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4821
- Accuracy: 0.7281
### 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon = 1e - 08 and optimizer_args = No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 12000
#### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.2516 | 0.0026 | 31 | 4.2449 | 0.0134 |
| 4.2382 | 1.0026 | 62 | 4.2149 | 0.0268 |
| 4.2199 | 2.0026 | 93 | 4.2137 | 0.0201 |
| 4.2282 | 3.0026 | 124 | 4.2076 | 0.0134 |
| 4.2281 | 4.0026 | 155 | 4.2019 | 0.0201 |
| 4.2196 | 5.0026 | 186 | 4.1915 | 0.0336 |
| 4.1905 | 6.0026 | 217 | 4.1647 | 0.0336 |
| 4.0539 | 7.0026 | 248 | 4.0414 | 0.0403 |
| 3.7809 | 8.0026 | 279 | 3.8345 | 0.0940 |
| 3.4673 | 9.0026 | 310 | 3.5941 | 0.1477 |
| 2.9501 | 10.0026 | 341 | 3.1686 | 0.2886 |
| 2.6627 | 11.0026 | 372 | 2.9001 | 0.3423 |
| 2.2112 | 12.0026 | 403 | 2.5710 | 0.4295 |
| 1.8892 | 13.0026 | 434 | 2.2780 | 0.5235 |
| 1.4221 | 14.0026 | 465 | 2.1011 | 0.5570 |
| 1.211 | 15.0026 | 496 | 1.9081 | 0.6242 |
| 0.9595 | 16.0026 | 527 | 1.7780 | 0.5705 |
| 0.6491 | 17.0026 | 558 | 1.6338 | 0.6376 |
| 0.507 | 18.0026 | 589 | 1.5465 | 0.5839 |
| 0.3488 | 19.0026 | 620 | 1.3768 | 0.6309 |
| 0.323 | 20.0026 | 651 | 1.5030 | 0.6040 |
| 0.2706 | 21.0026 | 682 | 1.2643 | 0.6644 |
| 0.2103 | 22.0026 | 713 | 1.4134 | 0.6309 |
| 0.2031 | 23.0026 | 744 | 1.1901 | 0.6779 |
| 0.1598 | 24.0026 | 775 | 1.3051 | 0.6644 |
| 0.1487 | 25.0026 | 806 | 1.0602 | 0.7584 |
| 0.1974 | 26.0026 | 837 | 1.4135 | 0.6309 |
| 0.0994 | 27.0026 | 868 | 1.3057 | 0.6309 |
| 0.1227 | 28.0026 | 899 | 1.1826 | 0.7114 |
| 0.1068 | 29.0026 | 930 | 1.2794 | 0.6711 |
| 0.1462 | 30.0026 | 961 | 1.2636 | 0.6443 |
| 0.1686 | 31.0026 | 992 | 1.2591 | 0.6644 |
| 0.0809 | 32.0026 | 1023 | 1.2660 | 0.6443 |
| 0.1183 | 33.0026 | 1054 | 1.3076 | 0.6376 |
| 0.1129 | 34.0026 | 1085 | 1.3627 | 0.6376 |
| 0.1875 | 35.0026 | 1116 | 1.2035 | 0.6846 |
| 0.1144 | 36.0026 | 1147 | 1.1673 | 0.6846 |
| 0.1495 | 37.0026 | 1178 | 0.9808 | 0.7248 |
| 0.0794 | 38.0026 | 1209 | 1.3220 | 0.6443 |
| 0.048 | 39.0026 | 1240 | 1.2628 | 0.6711 |
| 0.14 | 40.0026 | 1271 | 1.3869 | 0.6309 |
| 0.1426 | 41.0026 | 1302 | 1.0181 | 0.7450 |
| 0.0797 | 42.0026 | 1333 | 1.2371 | 0.6980 |
| 0.1119 | 43.0026 | 1364 | 1.6659 | 0.6242 |
| 0.058 | 44.0026 | 1395 | 1.2526 | 0.6644 |
| 0.0761 | 45.0026 | 1426 | 1.4394 | 0.6644 |
| 0.0626 | 46.0026 | 1457 | 1.3870 | 0.6913 |
| 0.1413 | 47.0026 | 1488 | 1.1319 | 0.7114 |
| 0.134 | 48.0026 | 1519 | 1.1347 | 0.6980 |
| 0.027 | 49.0026 | 1550 | 1.3457 | 0.6980 |
| 0.0302 | 50.0026 | 1581 | 1.2009 | 0.7248 |
| 0.0854 | 51.0026 | 1612 | 1.2139 | 0.7315 |
| 0.0258 | 52.0026 | 1643 | 1.3329 | 0.6577 |
| 0.1034 | 53.0026 | 1674 | 0.9688 | 0.7517 |
| 0.0926 | 54.0026 | 1705 | 1.1885 | 0.7114 |
| 0.1249 | 55.0026 | 1736 | 1.3345 | 0.6846 |
| 0.0478 | 56.0026 | 1767 | 1.5889 | 0.6577 |
| 0.0434 | 57.0026 | 1798 | 1.2202 | 0.7450 |
| 0.0649 | 58.0026 | 1829 | 1.1420 | 0.7517 |
| 0.0441 | 59.0026 | 1860 | 1.2257 | 0.7315 |
| 0.0069 | 60.0026 | 1891 | 1.2855 | 0.7114 |
| 0.0326 | 61.0026 | 1922 | 1.5572 | 0.6644 |
| 0.0208 | 62.0026 | 1953 | 1.4923 | 0.6846 |
| 0.0137 | 63.0026 | 1984 | 0.9975 | 0.7651 |
| 0.0186 | 64.0026 | 2015 | 1.1316 | 0.7114 |
| 0.0098 | 65.0026 | 2046 | 1.3824 | 0.6779 |
| 0.0053 | 66.0026 | 2077 | 1.1830 | 0.7248 |
| 0.0079 | 67.0026 | 2108 | 1.1329 | 0.7517 |
| 0.0085 | 68.0026 | 2139 | 1.3466 | 0.7114 |
| 0.0088 | 69.0026 | 2170 | 1.0010 | 0.7718 |
| 0.0239 | 70.0026 | 2201 | 1.3683 | 0.6779 |
| 0.0059 | 71.0026 | 2232 | 1.2557 | 0.7383 |
| 0.0361 | 72.0026 | 2263 | 1.5913 | 0.5973 |
| 0.0304 | 73.0026 | 2294 | 1.3168 | 0.7248 |
| 0.0125 | 74.0026 | 2325 | 1.1882 | 0.7047 |
| 0.1021 | 75.0026 | 2356 | 1.8726 | 0.5906 |
| 0.051 | 76.0026 | 2387 | 1.3520 | 0.6913 |
| 0.0113 | 77.0026 | 2418 | 1.1721 | 0.7248 |
| 0.0157 | 78.0026 | 2449 | 1.1814 | 0.7517 |
| 0.0193 | 79.0026 | 2480 | 1.2136 | 0.7248 |
| 0.0069 | 80.0026 | 2511 | 1.2597 | 0.7248 |
| 0.0252 | 81.0026 | 2542 | 1.4323 | 0.6779 |
| 0.0031 | 82.0026 | 2573 | 1.2964 | 0.7584 |
| 0.003 | 83.0026 | 2604 | 1.1853 | 0.7517 |
| 0.0105 | 84.0026 | 2635 | 1.1363 | 0.7517 |
| 0.003 | 85.0026 | 2666 | 1.2612 | 0.7383 |
| 0.0337 | 86.0026 | 2697 | 1.2846 | 0.7248 |
| 0.0069 | 87.0026 | 2728 | 1.7682 | 0.6846 |
| 0.0117 | 88.0026 | 2759 | 1.4233 | 0.7383 |
| 0.0052 | 89.0026 | 2790 | 1.3981 | 0.7248 |
| 0.0397 | 90.0026 | 2821 | 1.4646 | 0.6980 |
| 0.0034 | 91.0026 | 2852 | 1.0562 | 0.7718 |
| 0.077 | 92.0026 | 2883 | 1.1682 | 0.7517 |
| 0.0065 | 93.0026 | 2914 | 1.5453 | 0.7383 |
| 0.0333 | 94.0026 | 2945 | 1.5624 | 0.7114 |
| 0.0052 | 95.0026 | 2976 | 1.3218 | 0.7383 |
| 0.0471 | 96.0026 | 3007 | 1.2380 | 0.7517 |
| 0.0194 | 97.0026 | 3038 | 1.1390 | 0.7584 |
| 0.0098 | 98.0026 | 3069 | 1.2800 | 0.7651 |
| 0.0056 | 99.0026 | 3100 | 1.3672 | 0.7651 |
| 0.0234 | 100.0026 | 3131 | 1.1982 | 0.7718 |
| 0.0207 | 101.0026 | 3162 | 1.1749 | 0.7785 |
| 0.0178 | 102.0026 | 3193 | 1.1971 | 0.7584 |
| 0.0012 | 103.0026 | 3224 | 1.4601 | 0.7383 |
| 0.0007 | 104.0026 | 3255 | 1.3529 | 0.7651 |
| 0.0007 | 105.0026 | 3286 | 1.2458 | 0.7718 |
| 0.0031 | 106.0026 | 3317 | 1.0980 | 0.7785 |
| 0.0009 | 107.0026 | 3348 | 1.2404 | 0.7651 |
| 0.0066 | 108.0026 | 3379 | 1.4581 | 0.7047 |
| 0.0176 | 109.0026 | 3410 | 1.3197 | 0.7181 |
| 0.0022 | 110.0026 | 3441 | 1.1781 | 0.7651 |
| 0.0087 | 111.0026 | 3472 | 0.9605 | 0.7852 |
| 0.0008 | 112.0026 | 3503 | 1.3148 | 0.7248 |
| 0.0049 | 113.0026 | 3534 | 1.1561 | 0.7517 |
| 0.0338 | 114.0026 | 3565 | 1.2139 | 0.7315 |
| 0.0474 | 115.0026 | 3596 | 0.9615 | 0.8121 |
| 0.0135 | 116.0026 | 3627 | 1.4574 | 0.7181 |
| 0.0337 | 117.0026 | 3658 | 1.2884 | 0.7047 |
| 0.0522 | 118.0026 | 3689 | 1.6535 | 0.6577 |
| 0.0131 | 119.0026 | 3720 | 1.2566 | 0.7383 |
| 0.0015 | 120.0026 | 3751 | 1.4322 | 0.7181 |
| 0.003 | 121.0026 | 3782 | 1.1393 | 0.7651 |
| 0.0439 | 122.0026 | 3813 | 1.2454 | 0.7383 |
| 0.0057 | 123.0026 | 3844 | 1.1166 | 0.8054 |
| 0.0023 | 124.0026 | 3875 | 1.0567 | 0.7987 |
| 0.0139 | 125.0026 | 3906 | 1.0584 | 0.7517 |
| 0.0336 | 126.0026 | 3937 | 1.0674 | 0.7718 |
| 0.0014 | 127.0026 | 3968 | 1.1596 | 0.7718 |
| 0.0048 | 128.0026 | 3999 | 0.8337 | 0.8121 |
| 0.0004 | 129.0026 | 4030 | 1.0676 | 0.8054 |
| 0.0076 | 130.0026 | 4061 | 0.8792 | 0.8121 |
| 0.0031 | 131.0026 | 4092 | 0.8429 | 0.8389 |
| 0.0102 | 132.0026 | 4123 | 1.0233 | 0.8054 |
| 0.0006 | 133.0026 | 4154 | 0.9853 | 0.8054 |
| 0.0003 | 134.0026 | 4185 | 0.9309 | 0.8322 |
| 0.001 | 135.0026 | 4216 | 1.2404 | 0.7517 |
| 0.0067 | 136.0026 | 4247 | 1.1084 | 0.7718 |
| 0.0011 | 137.0026 | 4278 | 1.2728 | 0.7383 |
| 0.0047 | 138.0026 | 4309 | 1.2344 | 0.7718 |
| 0.0181 | 139.0026 | 4340 | 1.1505 | 0.7785 |
| 0.0021 | 140.0026 | 4371 | 1.1809 | 0.7181 |
| 0.0153 | 141.0026 | 4402 | 1.4485 | 0.6913 |
| 0.0356 | 142.0026 | 4433 | 1.6288 | 0.6846 |
| 0.0051 | 143.0026 | 4464 | 1.2842 | 0.7248 |
| 0.0105 | 144.0026 | 4495 | 1.3314 | 0.7450 |
| 0.0812 | 145.0026 | 4526 | 1.3686 | 0.7315 |
| 0.0005 | 146.0026 | 4557 | 1.2099 | 0.7450 |
| 0.005 | 147.0026 | 4588 | 1.3219 | 0.7584 |
| 0.0028 | 148.0026 | 4619 | 1.2283 | 0.7383 |
| 0.0411 | 149.0026 | 4650 | 1.2823 | 0.7651 |
| 0.0415 | 150.0026 | 4681 | 1.3887 | 0.7383 |
| 0.0117 | 151.0026 | 4712 | 1.3355 | 0.7517 |
| 0.0409 | 152.0026 | 4743 | 1.2657 | 0.7718 |
| 0.0047 | 153.0026 | 4774 | 1.1535 | 0.7785 |
| 0.0412 | 154.0026 | 4805 | 1.1267 | 0.7651 |
| 0.0105 | 155.0026 | 4836 | 1.2140 | 0.7785 |
| 0.0014 | 156.0026 | 4867 | 1.0343 | 0.8054 |
| 0.0105 | 157.0026 | 4898 | 1.3774 | 0.7315 |
| 0.0393 | 158.0026 | 4929 | 1.1731 | 0.7718 |
| 0.0063 | 159.0026 | 4960 | 1.4566 | 0.7315 |
| 0.0296 | 160.0026 | 4991 | 1.4041 | 0.7047 |
| 0.009 | 161.0026 | 5022 | 1.8027 | 0.6980 |
| 0.0014 | 162.0026 | 5053 | 1.3827 | 0.7315 |
| 0.0007 | 163.0026 | 5084 | 1.3005 | 0.7450 |
| 0.0015 | 164.0026 | 5115 | 1.2469 | 0.7517 |
| 0.0004 | 165.0026 | 5146 | 1.3470 | 0.7315 |
| 0.036 | 166.0026 | 5177 | 1.2124 | 0.7718 |
| 0.001 | 167.0026 | 5208 | 1.1371 | 0.7651 |
| 0.0123 | 168.0026 | 5239 | 1.0661 | 0.7785 |
| 0.0009 | 169.0026 | 5270 | 1.1514 | 0.7584 |
| 0.0004 | 170.0026 | 5301 | 1.2326 | 0.7248 |
| 0.0006 | 171.0026 | 5332 | 1.0440 | 0.7651 |
| 0.0002 | 172.0026 | 5363 | 1.1607 | 0.7718 |
| 0.0003 | 173.0026 | 5394 | 1.0651 | 0.7584 |
| 0.0003 | 174.0026 | 5425 | 1.0344 | 0.7651 |
| 0.0002 | 175.0026 | 5456 | 0.9785 | 0.7785 |
| 0.0002 | 176.0026 | 5487 | 1.0049 | 0.7852 |
| 0.0002 | 177.0026 | 5518 | 0.9546 | 0.7919 |
| 0.0002 | 178.0026 | 5549 | 0.9435 | 0.7852 |
| 0.0002 | 179.0026 | 5580 | 0.9449 | 0.7852 |
| 0.0001 | 180.0026 | 5611 | 0.9410 | 0.7987 |
| 0.0002 | 181.0026 | 5642 | 0.9710 | 0.8188 |
| 0.0001 | 182.0026 | 5673 | 0.9471 | 0.7987 |
| 0.0001 | 183.0026 | 5704 | 1.0540 | 0.7919 |
| 0.0002 | 184.0026 | 5735 | 1.1313 | 0.7718 |
| 0.0003 | 185.0026 | 5766 | 1.0735 | 0.7651 |
| 0.0051 | 186.0026 | 5797 | 1.5357 | 0.7248 |
| 0.0003 | 187.0026 | 5828 | 1.5115 | 0.7383 |
| 0.0089 | 188.0026 | 5859 | 1.3344 | 0.7181 |
| 0.065 | 189.0026 | 5890 | 1.4112 | 0.7248 |
| 0.0066 | 190.0026 | 5921 | 1.1956 | 0.7248 |
| 0.0019 | 191.0026 | 5952 | 1.0895 | 0.7785 |
| 0.0021 | 192.0026 | 5983 | 1.2925 | 0.7181 |
| 0.0696 | 193.0026 | 6014 | 1.2081 | 0.7315 |
| 0.0216 | 194.0026 | 6045 | 1.3298 | 0.7450 |
| 0.0097 | 195.0026 | 6076 | 1.4500 | 0.7315 |
| 0.0019 | 196.0026 | 6107 | 1.4464 | 0.7047 |
| 0.0003 | 197.0026 | 6138 | 1.5205 | 0.7181 |
| 0.0459 | 198.0026 | 6169 | 1.4027 | 0.7651 |
| 0.0002 | 199.0026 | 6200 | 1.3025 | 0.7517 |
| 0.0005 | 200.0026 | 6231 | 1.4194 | 0.7315 |
| 0.0003 | 201.0026 | 6262 | 1.5214 | 0.7315 |
| 0.0003 | 202.0026 | 6293 | 1.5199 | 0.7383 |
| 0.0386 | 203.0026 | 6324 | 1.3650 | 0.7450 |
| 0.0017 | 204.0026 | 6355 | 1.3455 | 0.7517 |
| 0.0006 | 205.0026 | 6386 | 1.2486 | 0.7785 |
| 0.0007 | 206.0026 | 6417 | 1.1444 | 0.7785 |
| 0.0008 | 207.0026 | 6448 | 1.2239 | 0.7987 |
| 0.0002 | 208.0026 | 6479 | 1.3080 | 0.7651 |
| 0.0014 | 209.0026 | 6510 | 1.3474 | 0.7651 |
| 0.0016 | 210.0026 | 6541 | 1.2968 | 0.7718 |
| 0.0597 | 211.0026 | 6572 | 1.3470 | 0.7383 |
| 0.0069 | 212.0026 | 6603 | 1.2246 | 0.7248 |
| 0.0198 | 213.0026 | 6634 | 1.3099 | 0.7718 |
| 0.0017 | 214.0026 | 6665 | 1.3106 | 0.7517 |
| 0.033 | 215.0026 | 6696 | 1.1807 | 0.7718 |
| 0.0002 | 216.0026 | 6727 | 1.3349 | 0.7785 |
| 0.0002 | 217.0026 | 6758 | 1.3824 | 0.7248 |
| 0.0008 | 218.0026 | 6789 | 1.0538 | 0.8255 |
| 0.0002 | 219.0026 | 6820 | 1.1092 | 0.8322 |
| 0.0003 | 220.0026 | 6851 | 1.1588 | 0.8121 |
| 0.0001 | 221.0026 | 6882 | 1.1470 | 0.8188 |
| 0.0001 | 222.0026 | 6913 | 1.1039 | 0.8389 |
| 0.0002 | 223.0026 | 6944 | 1.1088 | 0.8255 |
| 0.0001 | 224.0026 | 6975 | 1.3123 | 0.7651 |
| 0.0004 | 225.0026 | 7006 | 1.3394 | 0.7651 |
| 0.0005 | 226.0026 | 7037 | 1.1872 | 0.7584 |
| 0.0002 | 227.0026 | 7068 | 1.0812 | 0.7718 |
| 0.0001 | 228.0026 | 7099 | 1.0897 | 0.7852 |
| 0.0222 | 229.0026 | 7130 | 1.2743 | 0.7785 |
| 0.01 | 230.0026 | 7161 | 1.5242 | 0.7114 |
| 0.0019 | 231.0026 | 7192 | 1.4789 | 0.7047 |
| 0.0004 | 232.0026 | 7223 | 1.3616 | 0.7785 |
| 0.0014 | 233.0026 | 7254 | 1.4406 | 0.7785 |
| 0.0064 | 234.0026 | 7285 | 1.2080 | 0.7517 |
| 0.0293 | 235.0026 | 7316 | 1.1224 | 0.7919 |
| 0.0002 | 236.0026 | 7347 | 1.2375 | 0.7450 |
| 0.0008 | 237.0026 | 7378 | 1.0250 | 0.7919 |
| 0.0042 | 238.0026 | 7409 | 1.0995 | 0.8188 |
| 0.0001 | 239.0026 | 7440 | 1.4448 | 0.7450 |
| 0.0013 | 240.0026 | 7471 | 1.2713 | 0.7852 |
| 0.0454 | 241.0026 | 7502 | 1.4608 | 0.7315 |
| 0.0072 | 242.0026 | 7533 | 1.5889 | 0.7248 |
| 0.0002 | 243.0026 | 7564 | 1.4743 | 0.7383 |
| 0.0002 | 244.0026 | 7595 | 1.5414 | 0.7450 |
| 0.0052 | 245.0026 | 7626 | 1.4323 | 0.7315 |
| 0.0112 | 246.0026 | 7657 | 1.2444 | 0.7383 |
| 0.0004 | 247.0026 | 7688 | 1.1093 | 0.7450 |
| 0.0045 | 248.0026 | 7719 | 1.0848 | 0.7718 |
| 0.0001 | 249.0026 | 7750 | 1.3045 | 0.7248 |
| 0.0112 | 250.0026 | 7781 | 1.1020 | 0.7517 |
| 0.0001 | 251.0026 | 7812 | 1.1235 | 0.7315 |
| 0.0001 | 252.0026 | 7843 | 1.1265 | 0.7584 |
| 0.0001 | 253.0026 | 7874 | 1.0675 | 0.7584 |
| 0.0004 | 254.0026 | 7905 | 1.1567 | 0.7987 |
| 0.0001 | 255.0026 | 7936 | 1.0066 | 0.7987 |
| 0.0001 | 256.0026 | 7967 | 1.0489 | 0.7987 |
| 0.0024 | 257.0026 | 7998 | 1.0356 | 0.7919 |
| 0.0006 | 258.0026 | 8029 | 1.1126 | 0.7718 |
| 0.0003 | 259.0026 | 8060 | 1.2257 | 0.7517 |
| 0.0002 | 260.0026 | 8091 | 1.0724 | 0.7987 |
| 0.0467 | 261.0026 | 8122 | 1.0753 | 0.7919 |
| 0.0402 | 262.0026 | 8153 | 1.0815 | 0.7987 |
| 0.0002 | 263.0026 | 8184 | 1.1571 | 0.8054 |
| 0.0001 | 264.0026 | 8215 | 1.1499 | 0.8054 |
| 0.0001 | 265.0026 | 8246 | 1.0672 | 0.8121 |
| 0.0001 | 266.0026 | 8277 | 1.0647 | 0.8121 |
| 0.0001 | 267.0026 | 8308 | 1.0555 | 0.8188 |
| 0.0001 | 268.0026 | 8339 | 0.9889 | 0.8121 |
| 0.0001 | 269.0026 | 8370 | 1.1656 | 0.8054 |
| 0.0001 | 270.0026 | 8401 | 1.1094 | 0.8054 |
| 0.0001 | 271.0026 | 8432 | 1.1761 | 0.7852 |
| 0.0001 | 272.0026 | 8463 | 1.1401 | 0.7852 |
| 0.0001 | 273.0026 | 8494 | 1.2372 | 0.8054 |
| 0.0001 | 274.0026 | 8525 | 1.2034 | 0.7852 |
| 0.0001 | 275.0026 | 8556 | 1.1099 | 0.8121 |
| 0.0001 | 276.0026 | 8587 | 1.1181 | 0.8121 |
| 0.0004 | 277.0026 | 8618 | 1.2636 | 0.7987 |
| 0.0001 | 278.0026 | 8649 | 1.2969 | 0.7919 |
| 0.0001 | 279.0026 | 8680 | 1.2581 | 0.7987 |
| 0.0001 | 280.0026 | 8711 | 1.1910 | 0.7852 |
| 0.0001 | 281.0026 | 8742 | 1.2557 | 0.7852 |
| 0.0002 | 282.0026 | 8773 | 1.3032 | 0.7383 |
| 0.0001 | 283.0026 | 8804 | 1.2660 | 0.7852 |
| 0.0018 | 284.0026 | 8835 | 1.0920 | 0.8054 |
| 0.0001 | 285.0026 | 8866 | 1.1482 | 0.7651 |
| 0.0001 | 286.0026 | 8897 | 1.1187 | 0.7785 |
| 0.0001 | 287.0026 | 8928 | 1.0977 | 0.7785 |
| 0.0143 | 288.0026 | 8959 | 1.0366 | 0.7852 |
| 0.0001 | 289.0026 | 8990 | 1.1588 | 0.7785 |
| 0.0001 | 290.0026 | 9021 | 1.1447 | 0.7987 |
| 0.0001 | 291.0026 | 9052 | 1.1552 | 0.7987 |
| 0.0001 | 292.0026 | 9083 | 1.0919 | 0.8054 |
| 0.0001 | 293.0026 | 9114 | 1.1463 | 0.8054 |
| 0.0001 | 294.0026 | 9145 | 1.0648 | 0.8054 |
| 0.0001 | 295.0026 | 9176 | 1.0909 | 0.7987 |
| 0.0001 | 296.0026 | 9207 | 1.0817 | 0.7987 |
| 0.0001 | 297.0026 | 9238 | 1.0799 | 0.7987 |
| 0.0 | 298.0026 | 9269 | 1.0605 | 0.7987 |
| 0.0001 | 299.0026 | 9300 | 1.1082 | 0.7987 |
| 0.0001 | 300.0026 | 9331 | 1.0973 | 0.8054 |
| 0.0001 | 301.0026 | 9362 | 1.0669 | 0.7987 |
| 0.0001 | 302.0026 | 9393 | 1.0724 | 0.7987 |
| 0.0 | 303.0026 | 9424 | 1.0587 | 0.7987 |
| 0.0 | 304.0026 | 9455 | 1.0554 | 0.7987 |
| 0.0 | 305.0026 | 9486 | 1.0789 | 0.7987 |
| 0.0 | 306.0026 | 9517 | 1.0630 | 0.7987 |
| 0.0001 | 307.0026 | 9548 | 1.0515 | 0.7987 |
| 0.0001 | 308.0026 | 9579 | 1.1023 | 0.7987 |
| 0.0 | 309.0026 | 9610 | 1.0297 | 0.7987 |
| 0.0001 | 310.0026 | 9641 | 1.3142 | 0.7718 |
| 0.0001 | 311.0026 | 9672 | 1.2724 | 0.7852 |
| 0.0001 | 312.0026 | 9703 | 1.1862 | 0.7852 |
| 0.0001 | 313.0026 | 9734 | 1.1066 | 0.7987 |
| 0.0 | 314.0026 | 9765 | 1.0727 | 0.7919 |
| 0.0 | 315.0026 | 9796 | 1.1358 | 0.7919 |
| 0.0 | 316.0026 | 9827 | 1.0792 | 0.7987 |
| 0.0 | 317.0026 | 9858 | 1.0401 | 0.7852 |
| 0.0001 | 318.0026 | 9889 | 1.0561 | 0.7919 |
| 0.0002 | 319.0026 | 9920 | 1.0660 | 0.8121 |
| 0.0 | 320.0026 | 9951 | 1.0812 | 0.8255 |
| 0.0001 | 321.0026 | 9982 | 1.0705 | 0.8188 |
| 0.0001 | 322.0026 | 10013 | 1.0631 | 0.8188 |
| 0.0001 | 323.0026 | 10044 | 1.0629 | 0.8054 |
| 0.0 | 324.0026 | 10075 | 1.0619 | 0.8121 |
| 0.0001 | 325.0026 | 10106 | 1.1408 | 0.7919 |
| 0.0 | 326.0026 | 10137 | 1.1122 | 0.8121 |
| 0.0001 | 327.0026 | 10168 | 1.3270 | 0.7517 |
| 0.0001 | 328.0026 | 10199 | 1.3256 | 0.7450 |
| 0.0001 | 329.0026 | 10230 | 1.2374 | 0.7584 |
| 0.0224 | 330.0026 | 10261 | 1.2540 | 0.7383 |
| 0.0001 | 331.0026 | 10292 | 1.2998 | 0.7852 |
| 0.0 | 332.0026 | 10323 | 1.2713 | 0.7718 |
| 0.0001 | 333.0026 | 10354 | 1.2456 | 0.7919 |
| 0.0 | 334.0026 | 10385 | 1.1749 | 0.7987 |
| 0.0001 | 335.0026 | 10416 | 1.2139 | 0.7785 |
| 0.0 | 336.0026 | 10447 | 1.1159 | 0.7785 |
| 0.0 | 337.0026 | 10478 | 1.2492 | 0.8121 |
| 0.0001 | 338.0026 | 10509 | 1.4560 | 0.7651 |
| 0.0 | 339.0026 | 10540 | 1.4192 | 0.7651 |
| 0.0001 | 340.0026 | 10571 | 1.3882 | 0.7785 |
| 0.0 | 341.0026 | 10602 | 1.3044 | 0.7919 |
| 0.0001 | 342.0026 | 10633 | 1.3120 | 0.7987 |
| 0.0 | 343.0026 | 10664 | 1.3310 | 0.7987 |
| 0.0001 | 344.0026 | 10695 | 1.3061 | 0.7987 |
| 0.0 | 345.0026 | 10726 | 1.3386 | 0.8054 |
| 0.0001 | 346.0026 | 10757 | 1.2427 | 0.8054 |
| 0.0 | 347.0026 | 10788 | 1.2524 | 0.8054 |
| 0.0 | 348.0026 | 10819 | 1.2157 | 0.8121 |
| 0.0 | 349.0026 | 10850 | 1.2623 | 0.8121 |
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