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leandroZanatta27
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videomae-base-furtos

Video Classification
Transformers
TensorBoard
Safetensors
videomae
Generated from Trainer
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End of training

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  1. README.md +11 -7
  2. model.safetensors +1 -1
  3. runs/Sep05_12-58-42_leandro-pc/events.out.tfevents.1725551930.leandro-pc.61912.0 +2 -2
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: 0.4151
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- - Accuracy: 0.9
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  ## Model description
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@@ -45,16 +45,20 @@ 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: 8
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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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- | No log | 0.25 | 2 | 0.5630 | 0.95 |
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- | No log | 1.25 | 4 | 0.4741 | 0.9 |
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- | No log | 2.25 | 6 | 0.4301 | 0.9 |
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- | No log | 3.25 | 8 | 0.4151 | 0.9 |
 
 
 
 
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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: 0.3726
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+ - Accuracy: 0.95
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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: 64
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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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+ | No log | 0.125 | 8 | 0.7644 | 0.4 |
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+ | 0.7578 | 1.125 | 16 | 0.8079 | 0.55 |
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+ | 0.6084 | 2.125 | 24 | 0.7155 | 0.55 |
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+ | 0.6016 | 3.125 | 32 | 0.6016 | 0.6 |
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+ | 0.5236 | 4.125 | 40 | 0.6041 | 0.65 |
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+ | 0.5236 | 5.125 | 48 | 0.4796 | 0.75 |
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+ | 0.547 | 6.125 | 56 | 0.3917 | 0.95 |
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+ | 0.4097 | 7.125 | 64 | 0.3726 | 0.95 |
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  ### Framework versions
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