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End of training
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README.md
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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: vivit-videomae-d2
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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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# vivit-videomae-d2
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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: 2.3393
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- Accuracy: 0.3190
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 6650
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- mixed_precision_training: Native AMP
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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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| 2.5973 | 0.1 | 665 | 2.5600 | 0.0937 |
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| 2.5359 | 1.1 | 1330 | 2.4382 | 0.1767 |
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| 2.0681 | 2.1 | 1995 | 2.4175 | 0.2154 |
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| 2.2863 | 3.1 | 2660 | 2.3472 | 0.2166 |
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| 2.1409 | 4.1 | 3325 | 2.4337 | 0.2049 |
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| 2.1223 | 5.1 | 3990 | 2.3414 | 0.2821 |
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| 2.041 | 6.1 | 4655 | 2.2474 | 0.2054 |
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| 1.4722 | 7.1 | 5320 | 2.3306 | 0.2925 |
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| 1.9404 | 8.1 | 5985 | 2.4100 | 0.2897 |
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| 1.5395 | 9.1 | 6650 | 2.3393 | 0.3190 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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