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PaaP
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videomae-base-finetuned-masa

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Model card Files
xet
 Metrics Community
PaaP commited on
Commit
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1 Parent(s): d204efe

End of training

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Files changed (5) hide show
  1. README.md +24 -6
  2. emissions.csv +1 -0
  3. model.safetensors +1 -1
  4. runs/Sep04_09-46-00_3d3d7d19998a/events.out.tfevents.1725443167.3d3d7d19998a.3611.0 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ 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: 2.5431
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- - Accuracy: 0.2
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  ## Model description
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@@ -38,21 +38,39 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0005
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
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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: 24
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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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- | 1.7686 | 0.5 | 12 | 3.5896 | 0.2 |
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- | 2.4364 | 1.5 | 24 | 2.5431 | 0.2 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 4.3612
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+ - Accuracy: 0.4
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 9e-05
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  - train_batch_size: 1
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  - eval_batch_size: 1
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  - seed: 42
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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: 240
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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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+ | 1.6826 | 0.05 | 12 | 1.7279 | 0.0 |
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+ | 1.2427 | 1.05 | 24 | 1.6551 | 0.4 |
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+ | 0.89 | 2.05 | 36 | 1.5625 | 0.4 |
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+ | 1.1683 | 3.05 | 48 | 2.1126 | 0.4 |
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+ | 0.8243 | 4.05 | 60 | 2.8933 | 0.2 |
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+ | 0.291 | 5.05 | 72 | 2.3560 | 0.2 |
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+ | 0.3028 | 6.05 | 84 | 3.6436 | 0.2 |
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+ | 0.0613 | 7.05 | 96 | 3.0208 | 0.4 |
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+ | 0.0053 | 8.05 | 108 | 3.6414 | 0.4 |
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+ | 0.003 | 9.05 | 120 | 3.9191 | 0.4 |
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+ | 0.0026 | 10.05 | 132 | 3.9548 | 0.4 |
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+ | 0.0016 | 11.05 | 144 | 4.1584 | 0.4 |
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+ | 0.0015 | 12.05 | 156 | 4.2011 | 0.4 |
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+ | 0.0015 | 13.05 | 168 | 4.2129 | 0.4 |
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+ | 0.0013 | 14.05 | 180 | 4.2635 | 0.4 |
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+ | 0.0014 | 15.05 | 192 | 4.3133 | 0.4 |
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+ | 0.0013 | 16.05 | 204 | 4.3490 | 0.4 |
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+ | 0.0011 | 17.05 | 216 | 4.3620 | 0.4 |
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+ | 0.0011 | 18.05 | 228 | 4.3611 | 0.4 |
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+ | 0.0013 | 19.05 | 240 | 4.3612 | 0.4 |
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  ### Framework versions
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