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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-action_detection |
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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-action_detection |
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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: 1.2662 |
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- Accuracy: 0.7243 |
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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: 15200 |
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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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| 1.0956 | 0.02 | 305 | 1.3464 | 0.4774 | |
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| 0.683 | 1.02 | 610 | 2.3774 | 0.3704 | |
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| 0.5519 | 2.02 | 915 | 2.1501 | 0.3128 | |
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| 1.5863 | 3.02 | 1220 | 2.7112 | 0.2387 | |
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| 0.8028 | 4.02 | 1525 | 1.5204 | 0.7037 | |
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| 1.1797 | 5.02 | 1830 | 2.6479 | 0.2963 | |
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| 1.185 | 6.02 | 2135 | 0.8982 | 0.7860 | |
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| 0.9516 | 7.02 | 2440 | 1.2030 | 0.6008 | |
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| 0.5755 | 8.02 | 2745 | 0.8003 | 0.8189 | |
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| 0.6815 | 9.02 | 3050 | 2.3653 | 0.4198 | |
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| 1.1649 | 10.02 | 3355 | 3.0645 | 0.4403 | |
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| 1.1024 | 11.02 | 3660 | 2.4187 | 0.4321 | |
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| 1.1158 | 12.02 | 3965 | 2.2631 | 0.5597 | |
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| 0.2375 | 13.02 | 4270 | 2.2977 | 0.5432 | |
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| 0.7445 | 14.02 | 4575 | 1.0086 | 0.7860 | |
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| 0.6555 | 15.02 | 4880 | 0.7161 | 0.8560 | |
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| 0.8807 | 16.02 | 5185 | 1.2404 | 0.6584 | |
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| 1.0477 | 17.02 | 5490 | 1.6849 | 0.6173 | |
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| 0.498 | 18.02 | 5795 | 2.0557 | 0.5844 | |
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| 0.5536 | 19.02 | 6100 | 2.0703 | 0.5967 | |
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| 0.2232 | 20.02 | 6405 | 2.7690 | 0.4856 | |
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| 0.5589 | 21.02 | 6710 | 0.9549 | 0.7243 | |
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| 0.3377 | 22.02 | 7015 | 0.6488 | 0.8189 | |
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| 0.7096 | 23.02 | 7320 | 1.6638 | 0.5556 | |
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| 0.1201 | 24.02 | 7625 | 1.6283 | 0.5761 | |
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| 0.136 | 25.02 | 7930 | 1.4397 | 0.5926 | |
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| 0.2558 | 26.02 | 8235 | 1.7421 | 0.5350 | |
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| 0.3245 | 27.02 | 8540 | 1.2982 | 0.6132 | |
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| 0.0029 | 28.02 | 8845 | 1.0594 | 0.7202 | |
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| 0.3272 | 29.02 | 9150 | 1.0833 | 0.8272 | |
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| 0.0841 | 30.02 | 9455 | 1.3230 | 0.5926 | |
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| 0.5595 | 31.02 | 9760 | 2.5545 | 0.5844 | |
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| 0.0837 | 32.02 | 10065 | 1.5960 | 0.6296 | |
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| 0.0127 | 33.02 | 10370 | 1.8149 | 0.5720 | |
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| 0.3622 | 34.02 | 10675 | 2.4455 | 0.4938 | |
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| 0.0006 | 35.02 | 10980 | 1.6700 | 0.6461 | |
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| 0.0027 | 36.02 | 11285 | 2.2488 | 0.5720 | |
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| 0.0544 | 37.02 | 11590 | 2.6388 | 0.5514 | |
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| 0.2504 | 38.02 | 11895 | 1.5352 | 0.6379 | |
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| 0.0149 | 39.02 | 12200 | 2.2851 | 0.5391 | |
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| 0.4035 | 40.02 | 12505 | 1.8876 | 0.5556 | |
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| 0.0008 | 41.02 | 12810 | 2.4479 | 0.5473 | |
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| 0.3176 | 42.02 | 13115 | 2.0729 | 0.6049 | |
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| 0.0007 | 43.02 | 13420 | 1.5171 | 0.6255 | |
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| 0.3948 | 44.02 | 13725 | 1.4067 | 0.6132 | |
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| 0.0016 | 45.02 | 14030 | 1.0621 | 0.7325 | |
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| 0.2173 | 46.02 | 14335 | 1.5515 | 0.6132 | |
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| 0.0007 | 47.02 | 14640 | 1.2523 | 0.7284 | |
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| 0.2819 | 48.02 | 14945 | 1.5618 | 0.6461 | |
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| 0.0004 | 49.02 | 15200 | 1.2662 | 0.7243 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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