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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: videomae-base-videoMAE |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# videomae-base-videoMAE |
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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: 0.0000 |
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- Accuracy: 1.0 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- F1: 1.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 4 |
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- eval_batch_size: 4 |
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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: 12850 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.5601 | 1.0 | 515 | 0.4608 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.6361 | 2.0 | 1030 | 2.9149 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| 0.1473 | 3.0 | 1545 | 0.0617 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0012 | 4.0 | 2060 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.096 | 5.0 | 2575 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.1104 | 6.0 | 3090 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.2175 | 7.0 | 3605 | 2.6599 | 0.6667 | 1.0 | 0.6667 | 0.8000 | |
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| 0.0004 | 8.0 | 4120 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.1348 | 9.0 | 4635 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0001 | 10.0 | 5150 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.1291 | 11.0 | 5665 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.174 | 12.0 | 6180 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0002 | 13.0 | 6695 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0001 | 14.0 | 7210 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 15.0 | 7725 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 16.0 | 8240 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 17.0 | 8755 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 18.0 | 9270 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 19.0 | 9785 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 20.0 | 10300 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 21.0 | 10815 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 22.0 | 11330 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 23.0 | 11845 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 24.0 | 12360 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0 | 24.9515 | 12850 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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