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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-face
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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-face
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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: 2.5315
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- Accuracy: 0.6389
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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: 2000
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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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| 1.8253 | 9.005 | 100 | 1.7977 | 0.1667 |
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| 1.6427 | 19.005 | 200 | 2.1211 | 0.1667 |
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| 1.0603 | 29.005 | 300 | 2.5370 | 0.1944 |
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| 0.6361 | 39.005 | 400 | 1.9683 | 0.4444 |
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| 0.7149 | 49.005 | 500 | 2.8125 | 0.3889 |
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| 0.3396 | 59.005 | 600 | 2.2497 | 0.5556 |
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| 0.3026 | 69.005 | 700 | 1.7178 | 0.6389 |
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| 0.3043 | 79.005 | 800 | 2.5029 | 0.6111 |
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| 0.1636 | 89.005 | 900 | 2.7748 | 0.6111 |
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| 0.1292 | 99.005 | 1000 | 2.1868 | 0.6389 |
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| 0.5229 | 109.005 | 1100 | 2.4543 | 0.6111 |
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| 0.0016 | 119.005 | 1200 | 1.7452 | 0.75 |
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| 0.0013 | 129.005 | 1300 | 2.5026 | 0.6111 |
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| 0.0011 | 139.005 | 1400 | 2.3153 | 0.6389 |
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| 0.0011 | 149.005 | 1500 | 1.7536 | 0.75 |
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| 0.0028 | 159.005 | 1600 | 2.5384 | 0.6389 |
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| 0.0605 | 169.005 | 1700 | 2.6368 | 0.6111 |
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| 0.2064 | 179.005 | 1800 | 2.3678 | 0.6667 |
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| 0.0013 | 189.005 | 1900 | 2.4561 | 0.6389 |
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| 0.0009 | 199.005 | 2000 | 2.5315 | 0.6389 |
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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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