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---
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library_name: transformers
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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-finetuned-ucf101-subset-hand
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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-finetuned-ucf101-subset-hand
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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: 0.5545
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- Accuracy: 0.9
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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: 3
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- eval_batch_size: 3
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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: 1600
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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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| 1.6621 | 11.0006 | 100 | 1.6555 | 0.2 |
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| 1.6996 | 22.0012 | 200 | 1.5660 | 0.4167 |
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| 0.886 | 33.0019 | 300 | 1.4698 | 0.4167 |
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| 0.6728 | 44.0025 | 400 | 0.7168 | 0.7833 |
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| 0.1659 | 55.0031 | 500 | 1.3954 | 0.6667 |
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| 0.1471 | 66.0037 | 600 | 1.7320 | 0.6 |
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| 0.0085 | 77.0044 | 700 | 1.4034 | 0.7333 |
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| 0.0613 | 88.005 | 800 | 1.1479 | 0.7 |
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| 0.1256 | 99.0056 | 900 | 1.3657 | 0.7 |
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| 0.194 | 111.0006 | 1000 | 1.0879 | 0.7 |
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| 0.1336 | 122.0012 | 1100 | 0.9304 | 0.8 |
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| 0.0605 | 133.0019 | 1200 | 0.6773 | 0.85 |
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| 0.0025 | 144.0025 | 1300 | 0.7631 | 0.7833 |
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| 0.0016 | 155.0031 | 1400 | 0.4629 | 0.9167 |
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| 0.1698 | 166.0037 | 1500 | 0.5422 | 0.9167 |
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| 0.0011 | 177.0044 | 1600 | 0.5545 | 0.9 |
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### Framework versions
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- Transformers 4.45.0
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- Pytorch 2.4.1+cu118
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- Datasets 3.0.0
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- Tokenizers 0.20.0
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