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asmaa1
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videomae-base-groub1-finetuned-SLT-subset

Video Classification
Transformers
PyTorch
videomae
Generated from Trainer
Inference Endpoints
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  1. README.md +24 -11
  2. pytorch_model.bin +1 -1
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: 2.7991
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- - Accuracy: 0.15
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-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: 60
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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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- | 3.4789 | 0.33 | 20 | 2.9609 | 0.1 |
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- | 3.1907 | 1.33 | 40 | 2.8686 | 0.15 |
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- | 2.9742 | 2.33 | 60 | 2.7991 | 0.15 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.33.0
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- - Pytorch 2.0.0
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- - Datasets 2.1.0
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  - Tokenizers 0.13.3
 
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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: 0.3056
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+ - Accuracy: 0.9767
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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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: 1008
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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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+ | 3.8889 | 0.06 | 64 | 3.6733 | 0.0465 |
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+ | 3.8474 | 1.06 | 128 | 3.7358 | 0.0698 |
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+ | 3.7886 | 2.06 | 192 | 3.6336 | 0.0465 |
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+ | 3.7398 | 3.06 | 256 | 3.5894 | 0.0698 |
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+ | 3.7363 | 4.06 | 320 | 3.4637 | 0.0698 |
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+ | 3.6345 | 5.06 | 384 | 3.3875 | 0.0698 |
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+ | 3.2723 | 6.06 | 448 | 3.2156 | 0.1163 |
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+ | 3.2814 | 7.06 | 512 | 2.7291 | 0.7209 |
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+ | 2.7245 | 8.06 | 576 | 1.9657 | 0.8140 |
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+ | 1.8616 | 9.06 | 640 | 1.2883 | 0.8837 |
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+ | 1.3802 | 10.06 | 704 | 0.8116 | 0.9302 |
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+ | 1.0416 | 11.06 | 768 | 0.5877 | 0.9535 |
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+ | 0.6415 | 12.06 | 832 | 0.4426 | 0.9767 |
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+ | 0.5546 | 13.06 | 896 | 0.3599 | 0.9767 |
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+ | 0.4495 | 14.06 | 960 | 0.3212 | 0.9767 |
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+ | 0.2214 | 15.05 | 1008 | 0.3056 | 0.9767 |
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  ### Framework versions
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+ - Transformers 4.33.3
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3
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