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Amit7Singh
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videomae-base-ssbd-trim-yolo

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
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  1. README.md +32 -17
  2. model.safetensors +1 -1
  3. runs/Apr24_19-56-38_e0d26c525230/events.out.tfevents.1713990943.e0d26c525230.685.3 +3 -0
README.md CHANGED
@@ -17,7 +17,7 @@ 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-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: 1.3670
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  - Accuracy: 0.7949
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  ## Model description
@@ -44,27 +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: 630
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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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- | 0.9077 | 0.0683 | 43 | 1.1114 | 0.5278 |
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- | 1.0662 | 1.0683 | 86 | 1.4397 | 0.25 |
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- | 0.7166 | 2.0683 | 129 | 1.1111 | 0.5556 |
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- | 0.5385 | 3.0683 | 172 | 1.4677 | 0.6111 |
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- | 0.5025 | 4.0683 | 215 | 1.3852 | 0.6667 |
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- | 0.8695 | 5.0683 | 258 | 0.8738 | 0.8056 |
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- | 0.5152 | 6.0683 | 301 | 1.6813 | 0.6944 |
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- | 0.1175 | 7.0683 | 344 | 1.2260 | 0.8333 |
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- | 0.5459 | 8.0683 | 387 | 1.5197 | 0.75 |
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- | 0.0563 | 9.0683 | 430 | 1.8295 | 0.7222 |
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- | 0.2366 | 10.0683 | 473 | 1.2773 | 0.7778 |
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- | 0.0009 | 11.0683 | 516 | 1.4973 | 0.7778 |
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- | 0.143 | 12.0683 | 559 | 1.5192 | 0.7778 |
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- | 0.0016 | 13.0683 | 602 | 1.8634 | 0.7222 |
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- | 0.0185 | 14.0444 | 630 | 1.8943 | 0.7222 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 1.5906
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  - Accuracy: 0.7949
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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: 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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runs/Apr24_19-56-38_e0d26c525230/events.out.tfevents.1713990943.e0d26c525230.685.3 ADDED
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