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beingbatman
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CTMAE-P2-V4-S4

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +101 -101
  2. model.safetensors +1 -1
README.md CHANGED
@@ -18,7 +18,7 @@ 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-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3410
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  - Accuracy: 0.8043
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  ## Model description
@@ -51,106 +51,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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- | 0.616 | 0.0100 | 131 | 0.7146 | 0.5435 |
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- | 0.3323 | 1.0100 | 262 | 1.1001 | 0.5435 |
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- | 1.1488 | 2.0100 | 393 | 2.0763 | 0.5435 |
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- | 0.9082 | 3.0100 | 524 | 1.0627 | 0.5435 |
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- | 1.2652 | 4.0100 | 655 | 1.6966 | 0.5435 |
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- | 0.7613 | 5.0100 | 786 | 1.8759 | 0.5435 |
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- | 0.9116 | 6.0100 | 917 | 1.6454 | 0.5435 |
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- | 1.6582 | 7.0100 | 1048 | 0.9699 | 0.5435 |
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- | 0.7468 | 8.0100 | 1179 | 1.6307 | 0.5435 |
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- | 0.8789 | 9.0100 | 1310 | 0.9443 | 0.5435 |
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- | 0.81 | 10.0100 | 1441 | 1.4963 | 0.5435 |
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- | 0.7004 | 11.0100 | 1572 | 1.8480 | 0.5435 |
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- | 0.5665 | 12.0100 | 1703 | 0.8387 | 0.5 |
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- | 1.1895 | 13.0100 | 1834 | 1.2005 | 0.5435 |
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- | 0.8649 | 14.0100 | 1965 | 1.7430 | 0.5435 |
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- | 0.8802 | 15.0100 | 2096 | 0.9707 | 0.5652 |
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- | 0.2501 | 16.0100 | 2227 | 1.1576 | 0.6087 |
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- | 0.8725 | 17.0100 | 2358 | 1.0442 | 0.6304 |
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- | 0.9453 | 18.0100 | 2489 | 0.9894 | 0.6304 |
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- | 1.7248 | 19.0100 | 2620 | 1.6375 | 0.5652 |
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- | 0.2817 | 20.0100 | 2751 | 1.0368 | 0.6304 |
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- | 0.6772 | 21.0100 | 2882 | 1.3358 | 0.6304 |
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- | 1.3923 | 22.0100 | 3013 | 1.3909 | 0.6304 |
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- | 1.4265 | 23.0100 | 3144 | 1.2330 | 0.6739 |
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- | 0.4863 | 24.0100 | 3275 | 1.4850 | 0.6087 |
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- | 0.1316 | 25.0100 | 3406 | 1.5050 | 0.6739 |
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- | 0.9525 | 26.0100 | 3537 | 1.4812 | 0.6957 |
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- | 0.2113 | 27.0100 | 3668 | 1.4415 | 0.6304 |
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- | 0.4792 | 28.0100 | 3799 | 2.0549 | 0.6522 |
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- | 1.0471 | 29.0100 | 3930 | 1.4842 | 0.7391 |
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- | 0.3505 | 30.0100 | 4061 | 1.3527 | 0.7391 |
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- | 0.3526 | 31.0100 | 4192 | 1.4764 | 0.7174 |
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- | 0.3419 | 32.0100 | 4323 | 1.4041 | 0.7391 |
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- | 0.0375 | 33.0100 | 4454 | 1.7291 | 0.6739 |
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- | 1.0635 | 34.0100 | 4585 | 1.4507 | 0.6957 |
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- | 0.707 | 35.0100 | 4716 | 1.6608 | 0.6957 |
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- | 0.0019 | 36.0100 | 4847 | 1.3637 | 0.7826 |
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- | 0.1368 | 37.0100 | 4978 | 1.1200 | 0.7826 |
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- | 0.0549 | 38.0100 | 5109 | 1.6044 | 0.6957 |
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- | 0.287 | 39.0100 | 5240 | 1.4096 | 0.7609 |
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- | 0.0003 | 40.0100 | 5371 | 1.8292 | 0.7174 |
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- | 0.2976 | 41.0100 | 5502 | 1.3409 | 0.8043 |
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- | 0.4826 | 42.0100 | 5633 | 1.6037 | 0.7609 |
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- | 0.0114 | 43.0100 | 5764 | 1.8875 | 0.6957 |
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- | 0.6565 | 44.0100 | 5895 | 2.7154 | 0.5870 |
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- | 0.2799 | 45.0100 | 6026 | 1.8199 | 0.6739 |
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- | 0.2965 | 46.0100 | 6157 | 2.2753 | 0.6304 |
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- | 0.2962 | 47.0100 | 6288 | 2.0551 | 0.6522 |
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- | 0.0023 | 48.0100 | 6419 | 1.8138 | 0.6739 |
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- | 0.3492 | 49.0100 | 6550 | 2.5136 | 0.6522 |
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- | 0.3975 | 50.0100 | 6681 | 1.9044 | 0.7391 |
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- | 0.0004 | 51.0100 | 6812 | 2.0855 | 0.6957 |
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- | 0.0003 | 52.0100 | 6943 | 1.9510 | 0.7609 |
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- | 0.5971 | 53.0100 | 7074 | 2.0774 | 0.6957 |
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- | 0.0428 | 54.0100 | 7205 | 1.8712 | 0.6957 |
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- | 0.0014 | 55.0100 | 7336 | 1.7428 | 0.7826 |
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- | 0.1816 | 56.0100 | 7467 | 1.9815 | 0.7391 |
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- | 0.0003 | 57.0100 | 7598 | 2.0227 | 0.7174 |
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- | 0.2256 | 58.0100 | 7729 | 1.9730 | 0.7174 |
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- | 0.0001 | 59.0100 | 7860 | 2.9287 | 0.6304 |
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- | 0.1414 | 60.0100 | 7991 | 1.9747 | 0.7174 |
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- | 0.0008 | 61.0100 | 8122 | 1.8762 | 0.7391 |
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- | 0.0001 | 62.0100 | 8253 | 2.4515 | 0.6739 |
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- | 0.3695 | 63.0100 | 8384 | 2.1910 | 0.6522 |
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- | 0.0002 | 64.0100 | 8515 | 2.4142 | 0.6957 |
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- | 0.0003 | 65.0100 | 8646 | 2.1164 | 0.7174 |
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- | 0.4563 | 66.0100 | 8777 | 2.3604 | 0.7174 |
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- | 0.0001 | 67.0100 | 8908 | 2.1706 | 0.7174 |
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- | 0.0001 | 68.0100 | 9039 | 2.2836 | 0.7391 |
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- | 0.0 | 69.0100 | 9170 | 2.6949 | 0.6739 |
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- | 0.0001 | 70.0100 | 9301 | 2.7253 | 0.6957 |
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- | 0.0 | 71.0100 | 9432 | 2.6271 | 0.6957 |
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- | 0.0 | 72.0100 | 9563 | 2.4835 | 0.7174 |
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- | 0.0 | 73.0100 | 9694 | 2.4868 | 0.6739 |
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- | 0.0001 | 74.0100 | 9825 | 2.0949 | 0.7609 |
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- | 0.0006 | 75.0100 | 9956 | 2.3935 | 0.7174 |
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- | 0.0001 | 76.0100 | 10087 | 2.2223 | 0.7174 |
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- | 0.0069 | 77.0100 | 10218 | 2.6877 | 0.6957 |
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- | 0.0001 | 78.0100 | 10349 | 2.4705 | 0.7174 |
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- | 0.0 | 79.0100 | 10480 | 2.4520 | 0.7174 |
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- | 0.3584 | 80.0100 | 10611 | 2.3643 | 0.7391 |
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- | 0.0 | 81.0100 | 10742 | 2.4682 | 0.7174 |
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- | 0.0 | 82.0100 | 10873 | 2.5286 | 0.6957 |
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- | 0.0 | 83.0100 | 11004 | 2.6561 | 0.6957 |
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- | 0.0 | 84.0100 | 11135 | 2.6440 | 0.6957 |
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- | 0.0 | 85.0100 | 11266 | 2.6445 | 0.6957 |
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- | 0.0001 | 86.0100 | 11397 | 2.4613 | 0.7174 |
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- | 0.074 | 87.0100 | 11528 | 2.6370 | 0.7174 |
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- | 0.0001 | 88.0100 | 11659 | 2.6872 | 0.7174 |
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- | 0.0 | 89.0100 | 11790 | 2.7753 | 0.6739 |
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- | 0.0 | 90.0100 | 11921 | 2.7925 | 0.6522 |
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- | 0.0 | 91.0100 | 12052 | 2.6049 | 0.6957 |
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- | 0.0 | 92.0100 | 12183 | 2.6582 | 0.7174 |
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- | 0.0 | 93.0100 | 12314 | 2.6473 | 0.7174 |
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- | 0.0 | 94.0100 | 12445 | 2.6663 | 0.7174 |
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- | 0.0 | 95.0100 | 12576 | 2.6756 | 0.7174 |
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- | 0.0 | 96.0100 | 12707 | 2.6805 | 0.7174 |
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- | 0.0 | 97.0100 | 12838 | 2.6876 | 0.7174 |
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- | 0.0 | 98.0100 | 12969 | 2.6865 | 0.7174 |
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- | 0.0 | 99.0062 | 13050 | 2.6877 | 0.7174 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
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+ - Loss: 1.4928
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  - Accuracy: 0.8043
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24
  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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+ | 0.6322 | 0.0100 | 131 | 0.6958 | 0.5435 |
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+ | 0.3448 | 1.0100 | 262 | 1.4634 | 0.5435 |
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+ | 1.1225 | 2.0100 | 393 | 2.0266 | 0.5435 |
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+ | 0.7246 | 3.0100 | 524 | 0.9006 | 0.5435 |
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+ | 1.2784 | 4.0100 | 655 | 1.6206 | 0.5435 |
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+ | 0.7234 | 5.0100 | 786 | 1.7217 | 0.5435 |
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+ | 0.7544 | 6.0100 | 917 | 1.4504 | 0.5435 |
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+ | 1.732 | 7.0100 | 1048 | 1.1581 | 0.5435 |
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+ | 0.8227 | 8.0100 | 1179 | 1.9053 | 0.5435 |
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+ | 0.7839 | 9.0100 | 1310 | 0.9410 | 0.5435 |
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+ | 0.8302 | 10.0100 | 1441 | 1.5093 | 0.5435 |
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+ | 0.6264 | 11.0100 | 1572 | 1.7408 | 0.5435 |
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+ | 0.5032 | 12.0100 | 1703 | 0.7154 | 0.5 |
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+ | 1.1847 | 13.0100 | 1834 | 1.1743 | 0.5435 |
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+ | 0.9721 | 14.0100 | 1965 | 1.7714 | 0.5435 |
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+ | 0.6003 | 15.0100 | 2096 | 0.8652 | 0.5870 |
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+ | 0.4912 | 16.0100 | 2227 | 1.7541 | 0.5435 |
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+ | 0.8106 | 17.0100 | 2358 | 1.0464 | 0.5652 |
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+ | 1.2365 | 18.0100 | 2489 | 0.7472 | 0.6739 |
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+ | 1.7469 | 19.0100 | 2620 | 1.3125 | 0.6304 |
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+ | 0.2345 | 20.0100 | 2751 | 1.0220 | 0.6087 |
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+ | 0.483 | 21.0100 | 2882 | 1.2559 | 0.6087 |
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+ | 1.5409 | 22.0100 | 3013 | 1.6619 | 0.5435 |
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+ | 1.1284 | 23.0100 | 3144 | 1.0519 | 0.6739 |
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+ | 0.4471 | 24.0100 | 3275 | 2.1155 | 0.5652 |
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+ | 0.2323 | 25.0100 | 3406 | 1.6991 | 0.6304 |
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+ | 0.871 | 26.0100 | 3537 | 1.4254 | 0.6957 |
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+ | 0.4976 | 27.0100 | 3668 | 1.8011 | 0.6304 |
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+ | 0.5621 | 28.0100 | 3799 | 1.6148 | 0.6739 |
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+ | 0.9854 | 29.0100 | 3930 | 1.4576 | 0.6522 |
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+ | 0.0018 | 30.0100 | 4061 | 1.5995 | 0.7174 |
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+ | 0.3031 | 31.0100 | 4192 | 1.5070 | 0.6957 |
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+ | 0.8871 | 32.0100 | 4323 | 1.7620 | 0.6522 |
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+ | 0.6212 | 33.0100 | 4454 | 1.7319 | 0.6739 |
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+ | 0.5674 | 34.0100 | 4585 | 1.8520 | 0.6739 |
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+ | 0.2845 | 35.0100 | 4716 | 1.8629 | 0.6522 |
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+ | 0.1611 | 36.0100 | 4847 | 1.7524 | 0.6522 |
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+ | 0.0779 | 37.0100 | 4978 | 1.5949 | 0.6739 |
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+ | 0.6805 | 38.0100 | 5109 | 2.1198 | 0.6739 |
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+ | 0.0297 | 39.0100 | 5240 | 2.1019 | 0.6739 |
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+ | 0.0005 | 40.0100 | 5371 | 2.3706 | 0.6739 |
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+ | 0.4209 | 41.0100 | 5502 | 1.3258 | 0.6957 |
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+ | 0.2219 | 42.0100 | 5633 | 1.9883 | 0.6957 |
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+ | 0.0184 | 43.0100 | 5764 | 2.0343 | 0.6522 |
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+ | 0.001 | 44.0100 | 5895 | 1.9996 | 0.6957 |
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+ | 0.4252 | 45.0100 | 6026 | 1.9136 | 0.6522 |
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+ | 0.0456 | 46.0100 | 6157 | 1.9553 | 0.6739 |
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+ | 0.375 | 47.0100 | 6288 | 1.9227 | 0.6957 |
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+ | 0.6046 | 48.0100 | 6419 | 2.6295 | 0.6087 |
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+ | 0.2836 | 49.0100 | 6550 | 1.7961 | 0.7174 |
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+ | 0.1522 | 50.0100 | 6681 | 1.3961 | 0.7826 |
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+ | 0.6705 | 51.0100 | 6812 | 1.7068 | 0.7391 |
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+ | 0.0005 | 52.0100 | 6943 | 1.7986 | 0.7391 |
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+ | 0.02 | 53.0100 | 7074 | 1.6991 | 0.7609 |
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+ | 0.0037 | 54.0100 | 7205 | 1.5867 | 0.7391 |
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+ | 0.2488 | 55.0100 | 7336 | 1.4928 | 0.8043 |
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+ | 0.0297 | 56.0100 | 7467 | 1.8699 | 0.7174 |
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+ | 0.0003 | 57.0100 | 7598 | 2.1014 | 0.7174 |
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+ | 0.0008 | 58.0100 | 7729 | 1.9651 | 0.6739 |
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+ | 0.2982 | 59.0100 | 7860 | 2.5969 | 0.6522 |
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+ | 0.3197 | 60.0100 | 7991 | 2.3923 | 0.6087 |
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+ | 0.012 | 61.0100 | 8122 | 2.4473 | 0.6522 |
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+ | 0.0002 | 62.0100 | 8253 | 2.1692 | 0.6957 |
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+ | 0.0002 | 63.0100 | 8384 | 2.3358 | 0.6739 |
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+ | 0.0001 | 64.0100 | 8515 | 2.6785 | 0.6739 |
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+ | 0.364 | 65.0100 | 8646 | 2.7085 | 0.6522 |
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+ | 0.0001 | 66.0100 | 8777 | 2.8955 | 0.6522 |
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+ | 0.0002 | 67.0100 | 8908 | 2.2053 | 0.7391 |
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+ | 0.0002 | 68.0100 | 9039 | 2.6436 | 0.6739 |
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+ | 0.0001 | 69.0100 | 9170 | 2.6494 | 0.6739 |
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+ | 0.0046 | 70.0100 | 9301 | 2.2621 | 0.7391 |
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+ | 0.0001 | 71.0100 | 9432 | 2.9285 | 0.6739 |
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+ | 0.0001 | 72.0100 | 9563 | 2.4097 | 0.6957 |
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+ | 0.0001 | 73.0100 | 9694 | 2.8739 | 0.6304 |
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+ | 0.0004 | 74.0100 | 9825 | 2.8154 | 0.6304 |
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+ | 0.3257 | 75.0100 | 9956 | 2.3350 | 0.6957 |
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+ | 0.0001 | 76.0100 | 10087 | 1.9011 | 0.7391 |
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+ | 0.0001 | 77.0100 | 10218 | 2.3655 | 0.7174 |
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+ | 0.0001 | 78.0100 | 10349 | 2.6572 | 0.6739 |
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+ | 0.0001 | 79.0100 | 10480 | 2.6350 | 0.6739 |
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+ | 0.4185 | 80.0100 | 10611 | 2.4854 | 0.7174 |
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+ | 0.0001 | 81.0100 | 10742 | 2.4658 | 0.7391 |
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+ | 0.0 | 82.0100 | 10873 | 2.6691 | 0.6957 |
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+ | 0.0001 | 83.0100 | 11004 | 2.7930 | 0.5870 |
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+ | 0.0001 | 84.0100 | 11135 | 2.5645 | 0.6957 |
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+ | 0.0001 | 85.0100 | 11266 | 2.5759 | 0.7174 |
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+ | 0.0 | 86.0100 | 11397 | 2.6901 | 0.6957 |
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+ | 0.0 | 87.0100 | 11528 | 2.6050 | 0.6957 |
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+ | 0.0 | 88.0100 | 11659 | 3.0276 | 0.6087 |
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+ | 0.0001 | 89.0100 | 11790 | 2.9324 | 0.6739 |
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+ | 0.0 | 90.0100 | 11921 | 2.9194 | 0.6739 |
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+ | 0.0 | 91.0100 | 12052 | 2.5726 | 0.7391 |
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+ | 0.0 | 92.0100 | 12183 | 2.8832 | 0.6739 |
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+ | 0.0001 | 93.0100 | 12314 | 3.0274 | 0.6304 |
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+ | 0.0001 | 94.0100 | 12445 | 2.8242 | 0.6957 |
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+ | 0.0 | 95.0100 | 12576 | 2.7715 | 0.6957 |
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+ | 0.0 | 96.0100 | 12707 | 2.7907 | 0.6957 |
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+ | 0.4392 | 97.0100 | 12838 | 2.7856 | 0.6957 |
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+ | 0.0 | 98.0100 | 12969 | 2.7755 | 0.6957 |
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+ | 0.0 | 99.0062 | 13050 | 2.7569 | 0.6957 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:addbea0dbc91f960c1fef13fc0b50cba402efa72a4b303c839561417d5299008
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  size 1215496208
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:776c3e39774bd94ba91e00ca0a2d5b5727d671a52e223e6e93dfa571dbfe57ee
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  size 1215496208