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README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5906
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- - Accuracy: 0.7949
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  ## Model description
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@@ -44,42 +44,42 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - training_steps: 1260
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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- | 0.2348 | 0.0341 | 43 | 1.7930 | 0.75 |
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- | 1.1336 | 1.0341 | 86 | 1.4309 | 0.75 |
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- | 0.2629 | 2.0341 | 129 | 1.1878 | 0.7778 |
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- | 1.2759 | 3.0341 | 172 | 1.4044 | 0.7222 |
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- | 0.4068 | 4.0341 | 215 | 2.2838 | 0.6111 |
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- | 0.714 | 5.0341 | 258 | 2.3137 | 0.6111 |
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- | 0.1451 | 6.0341 | 301 | 0.9033 | 0.7222 |
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- | 0.3348 | 7.0341 | 344 | 1.0010 | 0.7778 |
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- | 0.7536 | 8.0341 | 387 | 1.5692 | 0.7778 |
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- | 1.0716 | 9.0341 | 430 | 1.7043 | 0.7222 |
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- | 0.3429 | 10.0341 | 473 | 1.7795 | 0.6667 |
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- | 0.0033 | 11.0341 | 516 | 0.7424 | 0.8056 |
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- | 0.0028 | 12.0341 | 559 | 1.5670 | 0.7222 |
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- | 0.0016 | 13.0341 | 602 | 1.0247 | 0.8056 |
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- | 0.3274 | 14.0341 | 645 | 1.5135 | 0.7222 |
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- | 0.0013 | 15.0341 | 688 | 0.8802 | 0.8056 |
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- | 0.0006 | 16.0341 | 731 | 1.0755 | 0.8056 |
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- | 0.0006 | 17.0341 | 774 | 1.9521 | 0.6667 |
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- | 0.0006 | 18.0341 | 817 | 1.2750 | 0.75 |
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- | 0.0008 | 19.0341 | 860 | 1.4754 | 0.6944 |
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- | 0.0006 | 20.0341 | 903 | 0.8656 | 0.8611 |
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- | 0.0005 | 21.0341 | 946 | 1.0175 | 0.8333 |
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- | 0.3342 | 22.0341 | 989 | 1.4655 | 0.8056 |
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- | 0.0007 | 23.0341 | 1032 | 1.1942 | 0.8333 |
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- | 0.0004 | 24.0341 | 1075 | 1.4391 | 0.8056 |
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- | 0.0006 | 25.0341 | 1118 | 1.2287 | 0.8333 |
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- | 0.0004 | 26.0341 | 1161 | 1.1902 | 0.8056 |
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- | 0.0011 | 27.0341 | 1204 | 1.1793 | 0.8333 |
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- | 0.0036 | 28.0341 | 1247 | 1.1913 | 0.8333 |
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- | 0.0003 | 29.0103 | 1260 | 1.1927 | 0.8333 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0946
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+ - Accuracy: 0.9844
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 9090
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 0.6749 | 0.0333 | 303 | 0.7530 | 0.6452 |
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+ | 0.9597 | 1.0333 | 606 | 1.4679 | 0.7137 |
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+ | 0.5435 | 2.0333 | 909 | 0.4142 | 0.8992 |
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+ | 0.5258 | 3.0333 | 1212 | 0.8016 | 0.8226 |
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+ | 0.0066 | 4.0333 | 1515 | 0.3179 | 0.9194 |
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+ | 1.5098 | 5.0333 | 1818 | 1.1273 | 0.7702 |
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+ | 0.0016 | 6.0333 | 2121 | 0.1973 | 0.9637 |
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+ | 0.2736 | 7.0333 | 2424 | 1.0816 | 0.7984 |
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+ | 0.6896 | 8.0333 | 2727 | 0.4091 | 0.9194 |
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+ | 0.2791 | 9.0333 | 3030 | 0.2331 | 0.9597 |
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+ | 0.4142 | 10.0333 | 3333 | 0.3057 | 0.9315 |
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+ | 0.3853 | 11.0333 | 3636 | 0.3853 | 0.9274 |
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+ | 0.0004 | 12.0333 | 3939 | 0.1782 | 0.9718 |
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+ | 0.0164 | 13.0333 | 4242 | 0.5571 | 0.9032 |
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+ | 0.0002 | 14.0333 | 4545 | 0.1784 | 0.9597 |
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+ | 0.1403 | 15.0333 | 4848 | 0.1136 | 0.9758 |
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+ | 0.0003 | 16.0333 | 5151 | 0.1628 | 0.9677 |
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+ | 0.2939 | 17.0333 | 5454 | 0.1729 | 0.9718 |
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+ | 0.0001 | 18.0333 | 5757 | 0.1332 | 0.9718 |
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+ | 0.0002 | 19.0333 | 6060 | 0.2212 | 0.9637 |
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+ | 0.0007 | 20.0333 | 6363 | 0.4098 | 0.9274 |
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+ | 0.02 | 21.0333 | 6666 | 0.3855 | 0.9395 |
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+ | 0.0164 | 22.0333 | 6969 | 0.2359 | 0.9597 |
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+ | 0.0002 | 23.0333 | 7272 | 0.2383 | 0.9677 |
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+ | 0.0001 | 24.0333 | 7575 | 0.1351 | 0.9798 |
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+ | 0.1064 | 25.0333 | 7878 | 0.1471 | 0.9798 |
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+ | 0.0001 | 26.0333 | 8181 | 0.1395 | 0.9798 |
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+ | 0.0001 | 27.0333 | 8484 | 0.1639 | 0.9758 |
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+ | 0.0001 | 28.0333 | 8787 | 0.2662 | 0.9637 |
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+ | 0.0001 | 29.0333 | 9090 | 0.2468 | 0.9677 |
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  ### Framework versions
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