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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-large |
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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-cctv-brawl_extended_v2 |
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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-cctv-brawl_extended_v2 |
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This model is a fine-tuned version of [MCG-NJU/videomae-large](https://huggingface.co./MCG-NJU/videomae-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7025 |
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- Accuracy: 0.8993 |
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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-07 |
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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: 37695 |
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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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| 0.4212 | 0.07 | 2514 | 0.4737 | 0.7236 | |
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| 0.2813 | 1.07 | 5028 | 0.3922 | 0.8350 | |
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| 0.1918 | 2.07 | 7542 | 0.5665 | 0.8734 | |
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| 0.2002 | 3.07 | 10056 | 0.6058 | 0.8808 | |
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| 0.1921 | 4.07 | 12570 | 0.6136 | 0.8867 | |
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| 0.1713 | 5.07 | 15084 | 0.6446 | 0.8914 | |
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| 0.006 | 6.07 | 17598 | 0.6783 | 0.8918 | |
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| 0.004 | 7.07 | 20112 | 0.7586 | 0.8863 | |
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| 0.201 | 8.07 | 22626 | 0.7732 | 0.8906 | |
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| 0.0237 | 9.07 | 25140 | 0.7025 | 0.8993 | |
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| 0.0003 | 10.07 | 27654 | 0.7510 | 0.8957 | |
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| 0.1943 | 11.07 | 30168 | 0.7849 | 0.8989 | |
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| 0.0001 | 12.07 | 32682 | 0.8075 | 0.8981 | |
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| 0.0 | 13.07 | 35196 | 0.8347 | 0.8961 | |
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| 0.0001 | 14.07 | 37695 | 0.8329 | 0.8985 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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