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videomae-base-finetuned-Risky-situations

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
Inference Endpoints
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  1. README.md +13 -8
  2. model.safetensors +1 -1
  3. runs/Aug13_20-26-46_3438a655bd59/events.out.tfevents.1723580854.3438a655bd59.1027.2 +2 -2
  4. runs/Aug13_20-26-46_3438a655bd59/events.out.tfevents.1723582196.3438a655bd59.1027.3 +3 -0
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: 0.0012
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- - Accuracy: 1.0
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  ## Model description
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@@ -44,17 +44,22 @@ 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: 125
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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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- | 0.7248 | 0.2 | 25 | 0.3614 | 1.0 |
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- | 0.829 | 1.2 | 50 | 0.2228 | 0.9167 |
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- | 0.3176 | 2.2 | 75 | 0.0061 | 1.0 |
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- | 0.0027 | 3.2 | 100 | 0.0014 | 1.0 |
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- | 0.0011 | 4.2 | 125 | 0.0012 | 1.0 |
 
 
 
 
 
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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: 0.2880
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+ - Accuracy: 0.8462
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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: 250
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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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+ | 0.4854 | 0.1 | 25 | 0.0940 | 1.0 |
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+ | 0.2925 | 1.1 | 50 | 0.0021 | 1.0 |
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+ | 0.0187 | 2.1 | 75 | 0.3059 | 0.9167 |
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+ | 0.0004 | 3.1 | 100 | 2.2330 | 0.6667 |
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+ | 0.0005 | 4.1 | 125 | 0.0003 | 1.0 |
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+ | 0.0003 | 5.1 | 150 | 0.0003 | 1.0 |
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+ | 0.3102 | 6.1 | 175 | 1.2503 | 0.75 |
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+ | 0.0003 | 7.1 | 200 | 0.0002 | 1.0 |
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+ | 0.0002 | 8.1 | 225 | 0.0003 | 1.0 |
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+ | 0.0002 | 9.1 | 250 | 0.0004 | 1.0 |
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  ### Framework versions
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