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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-custom-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/v8zohmjq)
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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/v8zohmjq)
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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/v8zohmjq)
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# videomae-base-finetuned-kinetics-finetuned-custom-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: 0.9783
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- Accuracy: 0.7564
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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: 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: 710
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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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| 0.6747 | 0.1014 | 72 | 0.6989 | 0.7308 |
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| 0.5585 | 1.1014 | 144 | 0.7504 | 0.7308 |
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| 1.0181 | 2.1014 | 216 | 0.5370 | 0.6795 |
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| 0.5883 | 3.1014 | 288 | 0.6710 | 0.7308 |
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| 0.3918 | 4.1014 | 360 | 0.5803 | 0.7692 |
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| 0.3903 | 5.1014 | 432 | 0.5857 | 0.7436 |
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| 0.2452 | 6.1014 | 504 | 0.8492 | 0.7308 |
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| 0.4107 | 7.1014 | 576 | 0.8475 | 0.7308 |
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| 0.099 | 8.1014 | 648 | 0.9360 | 0.7436 |
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| 0.0679 | 9.0873 | 710 | 0.9783 | 0.7564 |
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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 2.13.2
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- Tokenizers 0.19.1
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