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---
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license: cc-by-nc-4.0
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base_model: MCG-NJU/videomae-base-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-base-finetuned-kinetics-finetuned-freeway-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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/3e8psy1e)
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# videomae-base-finetuned-kinetics-finetuned-freeway-subset
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This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0016
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- Accuracy: 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: 5
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- eval_batch_size: 5
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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: 1800
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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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| 0.6551 | 0.02 | 36 | 0.7171 | 0.5 |
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| 0.6085 | 1.02 | 72 | 0.7057 | 0.5 |
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| 0.5876 | 2.02 | 108 | 0.5834 | 0.75 |
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| 0.5757 | 3.02 | 144 | 0.5360 | 0.7143 |
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| 0.7017 | 4.02 | 180 | 0.4589 | 0.7143 |
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| 0.5681 | 5.02 | 216 | 0.3667 | 0.8214 |
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| 0.3418 | 6.02 | 252 | 0.2312 | 0.9286 |
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| 0.6408 | 7.02 | 288 | 0.2724 | 0.8929 |
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| 0.3846 | 8.02 | 324 | 0.1288 | 0.9643 |
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| 0.1551 | 9.02 | 360 | 0.6198 | 0.8214 |
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| 0.4879 | 10.02 | 396 | 0.3241 | 0.8571 |
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| 0.0982 | 11.02 | 432 | 0.1815 | 0.9286 |
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| 0.112 | 12.02 | 468 | 0.2504 | 0.9643 |
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| 0.3627 | 13.02 | 504 | 0.2357 | 0.9643 |
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| 0.2329 | 14.02 | 540 | 0.6101 | 0.8571 |
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| 0.141 | 15.02 | 576 | 0.0218 | 1.0 |
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| 0.1755 | 16.02 | 612 | 0.0791 | 0.9643 |
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| 0.079 | 17.02 | 648 | 0.1167 | 0.9643 |
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| 0.0859 | 18.02 | 684 | 0.0118 | 1.0 |
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| 0.0131 | 19.02 | 720 | 0.0020 | 1.0 |
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| 0.0014 | 20.02 | 756 | 0.0054 | 1.0 |
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| 0.0008 | 21.02 | 792 | 0.0841 | 0.9286 |
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| 0.0024 | 22.02 | 828 | 0.0852 | 0.9643 |
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| 0.1803 | 23.02 | 864 | 0.0005 | 1.0 |
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| 0.0001 | 24.02 | 900 | 0.0379 | 0.9643 |
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| 0.0012 | 25.02 | 936 | 0.0705 | 0.9643 |
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| 0.0018 | 26.02 | 972 | 0.0010 | 1.0 |
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| 0.0007 | 27.02 | 1008 | 0.0210 | 1.0 |
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| 0.0028 | 28.02 | 1044 | 0.0030 | 1.0 |
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| 0.0465 | 29.02 | 1080 | 0.0005 | 1.0 |
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| 0.0004 | 30.02 | 1116 | 0.0011 | 1.0 |
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| 0.0016 | 31.02 | 1152 | 0.0005 | 1.0 |
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| 0.0 | 32.02 | 1188 | 0.0012 | 1.0 |
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| 0.0002 | 33.02 | 1224 | 0.0001 | 1.0 |
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| 0.0315 | 34.02 | 1260 | 0.0027 | 1.0 |
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| 0.0253 | 35.02 | 1296 | 0.0003 | 1.0 |
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| 0.0011 | 36.02 | 1332 | 0.0022 | 1.0 |
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| 0.0001 | 37.02 | 1368 | 0.0006 | 1.0 |
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| 0.0007 | 38.02 | 1404 | 0.0120 | 1.0 |
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| 0.0001 | 39.02 | 1440 | 0.1001 | 0.9643 |
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| 0.0005 | 40.02 | 1476 | 0.0331 | 0.9643 |
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| 0.0009 | 41.02 | 1512 | 0.0418 | 0.9643 |
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| 0.0035 | 42.02 | 1548 | 0.0761 | 0.9643 |
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| 0.0001 | 43.02 | 1584 | 0.0020 | 1.0 |
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| 0.0001 | 44.02 | 1620 | 0.0020 | 1.0 |
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| 0.0 | 45.02 | 1656 | 0.0010 | 1.0 |
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| 0.0001 | 46.02 | 1692 | 0.0009 | 1.0 |
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| 0.0005 | 47.02 | 1728 | 0.0012 | 1.0 |
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| 0.0001 | 48.02 | 1764 | 0.0015 | 1.0 |
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| 0.0002 | 49.02 | 1800 | 0.0016 | 1.0 |
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### Framework versions
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- Transformers 4.42.0.dev0
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- Pytorch 2.1.1
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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