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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-large-finetuned-kinetics |
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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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model-index: |
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- name: MAE-CT-CPC-Dicotomized-v4-early-stop |
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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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# MAE-CT-CPC-Dicotomized-v4-early-stop |
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This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co./MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4282 |
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- Accuracy: 0.8293 |
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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: 1e-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: 1440 |
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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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| 0.5342 | 0.06 | 81 | 0.6496 | 0.6829 | |
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| 0.6266 | 1.06 | 162 | 0.5854 | 0.6829 | |
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| 0.6599 | 2.06 | 243 | 0.5206 | 0.6829 | |
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| 0.877 | 3.06 | 324 | 0.5995 | 0.6098 | |
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| 0.653 | 4.06 | 405 | 0.4908 | 0.7561 | |
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| 0.7604 | 5.06 | 486 | 0.4936 | 0.7805 | |
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| 0.4795 | 6.06 | 567 | 0.9528 | 0.6829 | |
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| 0.278 | 7.06 | 648 | 0.5565 | 0.8049 | |
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| 0.3548 | 8.06 | 729 | 0.5855 | 0.7561 | |
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| 0.4386 | 9.06 | 810 | 0.6578 | 0.7561 | |
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| 0.3007 | 10.06 | 891 | 0.6622 | 0.7805 | |
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| 0.313 | 11.06 | 972 | 0.8350 | 0.7561 | |
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| 0.0554 | 12.06 | 1053 | 1.0043 | 0.7073 | |
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| 0.2804 | 13.06 | 1134 | 1.0247 | 0.7073 | |
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| 0.1424 | 14.06 | 1215 | 0.8542 | 0.7805 | |
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| 0.4692 | 15.06 | 1296 | 1.0264 | 0.7317 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 3.0.1 |
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- Tokenizers 0.15.1 |
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