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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
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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
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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: 0.3988
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- Accuracy: 0.8714
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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: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.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: 148
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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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| 2.1392 | 0.2568 | 38 | 1.8769 | 0.4143 |
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| 1.0079 | 1.2568 | 76 | 0.9862 | 0.7286 |
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| 0.4814 | 2.2568 | 114 | 0.5106 | 0.8857 |
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| 0.3286 | 3.2297 | 148 | 0.3988 | 0.8714 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.4.1
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- Datasets 2.19.1
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- Tokenizers 0.20.0
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