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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: videomae-large-finetuned-kinetics-finetuned-videomae-large-kitchen |
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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-large-finetuned-kinetics-finetuned-videomae-large-kitchen |
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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: 0.6309 |
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- Accuracy: 0.8900 |
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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: 11100 |
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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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| 3.5158 | 0.02 | 222 | 3.6067 | 0.0588 | |
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| 2.8571 | 1.02 | 444 | 3.1445 | 0.3014 | |
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| 1.8854 | 2.02 | 666 | 2.3644 | 0.4607 | |
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| 1.5533 | 3.02 | 888 | 1.7967 | 0.5621 | |
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| 1.3935 | 4.02 | 1110 | 1.3755 | 0.6502 | |
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| 1.1722 | 5.02 | 1332 | 1.2232 | 0.7109 | |
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| 0.2896 | 6.02 | 1554 | 1.2859 | 0.6256 | |
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| 0.3166 | 7.02 | 1776 | 1.2910 | 0.6720 | |
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| 0.6902 | 8.02 | 1998 | 1.2702 | 0.6995 | |
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| 0.4193 | 9.02 | 2220 | 1.2087 | 0.7137 | |
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| 0.1889 | 10.02 | 2442 | 1.0500 | 0.7611 | |
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| 0.4502 | 11.02 | 2664 | 1.1647 | 0.7118 | |
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| 0.7703 | 12.02 | 2886 | 1.1037 | 0.7242 | |
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| 0.0957 | 13.02 | 3108 | 1.0967 | 0.7706 | |
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| 0.3202 | 14.02 | 3330 | 1.0479 | 0.7545 | |
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| 0.3634 | 15.02 | 3552 | 1.0714 | 0.8057 | |
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| 0.3883 | 16.02 | 3774 | 1.2323 | 0.7498 | |
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| 0.0322 | 17.02 | 3996 | 1.0504 | 0.7848 | |
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| 0.5108 | 18.02 | 4218 | 1.1356 | 0.7915 | |
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| 0.309 | 19.02 | 4440 | 1.1409 | 0.7592 | |
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| 0.56 | 20.02 | 4662 | 1.0828 | 0.7915 | |
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| 0.3675 | 21.02 | 4884 | 0.9154 | 0.8123 | |
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| 0.0076 | 22.02 | 5106 | 1.0974 | 0.8133 | |
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| 0.0451 | 23.02 | 5328 | 1.0361 | 0.8152 | |
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| 0.2558 | 24.02 | 5550 | 0.7830 | 0.8237 | |
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| 0.0125 | 25.02 | 5772 | 0.8728 | 0.8171 | |
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| 0.4184 | 26.02 | 5994 | 0.8413 | 0.8265 | |
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| 0.2566 | 27.02 | 6216 | 1.0644 | 0.8009 | |
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| 0.1257 | 28.02 | 6438 | 0.8641 | 0.8265 | |
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| 0.1326 | 29.02 | 6660 | 0.8444 | 0.8417 | |
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| 0.0436 | 30.02 | 6882 | 0.8615 | 0.8322 | |
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| 0.0408 | 31.02 | 7104 | 0.8075 | 0.8332 | |
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| 0.0316 | 32.02 | 7326 | 0.8699 | 0.8341 | |
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| 0.2235 | 33.02 | 7548 | 0.8151 | 0.8455 | |
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| 0.0079 | 34.02 | 7770 | 0.8099 | 0.8550 | |
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| 0.001 | 35.02 | 7992 | 0.8640 | 0.8370 | |
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| 0.0007 | 36.02 | 8214 | 0.7146 | 0.8483 | |
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| 0.464 | 37.02 | 8436 | 0.7917 | 0.8464 | |
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| 0.0005 | 38.02 | 8658 | 0.7239 | 0.8531 | |
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| 0.0004 | 39.02 | 8880 | 0.7702 | 0.8701 | |
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| 0.1705 | 40.02 | 9102 | 0.7543 | 0.8521 | |
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| 0.0039 | 41.02 | 9324 | 0.7456 | 0.8673 | |
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| 0.0168 | 42.02 | 9546 | 0.7255 | 0.8730 | |
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| 0.2615 | 43.02 | 9768 | 0.7453 | 0.8758 | |
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| 0.0004 | 44.02 | 9990 | 0.6824 | 0.8806 | |
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| 0.236 | 45.02 | 10212 | 0.6624 | 0.8825 | |
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| 0.0007 | 46.02 | 10434 | 0.6727 | 0.8815 | |
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| 0.0004 | 47.02 | 10656 | 0.6478 | 0.8863 | |
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| 0.268 | 48.02 | 10878 | 0.6309 | 0.8900 | |
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| 0.0025 | 49.02 | 11100 | 0.6284 | 0.8900 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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