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--- |
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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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model-index: |
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- name: videomae-base-finetuned-ucf101-subset |
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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-finetuned-ucf101-subset |
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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: 0.3585 |
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- Accuracy: 0.9226 |
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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: 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: 3750 |
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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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| 2.0046 | 0.04 | 150 | 2.0806 | 0.3143 | |
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| 1.9549 | 1.04 | 300 | 1.4746 | 0.5429 | |
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| 0.6873 | 2.04 | 450 | 0.9489 | 0.6714 | |
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| 1.6042 | 3.04 | 600 | 0.6865 | 0.7571 | |
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| 0.2082 | 4.04 | 750 | 0.4017 | 0.8857 | |
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| 0.2805 | 5.04 | 900 | 0.9705 | 0.7714 | |
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| 0.0062 | 6.04 | 1050 | 0.4833 | 0.8571 | |
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| 0.2727 | 7.04 | 1200 | 0.8048 | 0.8714 | |
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| 0.1055 | 8.04 | 1350 | 0.0264 | 0.9857 | |
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| 0.234 | 9.04 | 1500 | 0.1460 | 0.9714 | |
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| 0.0015 | 10.04 | 1650 | 0.3039 | 0.9429 | |
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| 0.0012 | 11.04 | 1800 | 0.2351 | 0.9571 | |
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| 0.0009 | 12.04 | 1950 | 0.3080 | 0.9286 | |
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| 0.0009 | 13.04 | 2100 | 0.3477 | 0.9429 | |
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| 0.036 | 14.04 | 2250 | 0.2366 | 0.9571 | |
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| 0.0008 | 15.04 | 2400 | 0.4506 | 0.9 | |
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| 0.0037 | 16.04 | 2550 | 0.2327 | 0.9571 | |
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| 0.0007 | 17.04 | 2700 | 0.3480 | 0.9286 | |
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| 0.0007 | 18.04 | 2850 | 0.1762 | 0.9714 | |
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| 0.0006 | 19.04 | 3000 | 0.0991 | 0.9714 | |
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| 0.0006 | 20.04 | 3150 | 0.1551 | 0.9714 | |
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| 0.0006 | 21.04 | 3300 | 0.3023 | 0.9429 | |
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| 0.0006 | 22.04 | 3450 | 0.1543 | 0.9571 | |
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| 0.0006 | 23.04 | 3600 | 0.1025 | 0.9571 | |
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| 0.0006 | 24.04 | 3750 | 0.0876 | 0.9571 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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